research methods chapter 5

Research Methods in Psychology - 4th American Edition

(40 reviews)

Carrie Cuttler, Washington State University

Rajiv S. Jhangiani, Kwantlen Polytechnic University

Dana C. Leighton, Texas A&M University, Texarkana

ISBN 13: 9781999198107

Publisher: Kwantlen Polytechnic University

Language: English

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Reviewed by Beth Mechlin, Associate Professor of Psychology & Neuroscience, Earlham College on 3/19/24

This is an extremely comprehensive text for an undergraduate psychology course about research methods. It does an excellent job covering the basics of a variety of types of research design. It also includes important topics related to research... read more

Comprehensiveness rating: 5 see less

Content Accuracy rating: 5

I did not notice any errors in this text.

Relevance/Longevity rating: 5

The content is very relevant. It will likely need to be updated over time in order to keep research examples relevant. Additionally, APA formatting guidelines may need to be updated when a new publication manual is released. However, these should be easy updates for the authors to make when the time comes.

Clarity rating: 5

This text is very clear and easy to follow. The explanations are easy for college students to understand. The authors use a lot of examples to help illustrate specific concepts. They also incorporate a variety of relevant outside sources (such as videos) to provide additional examples.

Consistency rating: 5

The text is consistent and flows well from one section to the next. At the end of each large section (similar to a chapter) the authors provide key takeaways and exercises.

Modularity rating: 5

This text is very modular. It is easy to pick and choose which sections you want to use in your course when. Each section can stand alone fairly easily.

Organization/Structure/Flow rating: 5

The text is very well organized. Information flows smoothly from one topic to the next.

Interface rating: 5

The interface is great. The text is easy to navigate and the images display well (I only noticed 1 image in which the formatting was a tad off).

Grammatical Errors rating: 5

I did not notice any grammatical errors.

Cultural Relevance rating: 5

The text is culturally relevant.

This is an excellent text for an undergraduate research methods course in the field of Psychology. I have been using the text for my Research Methods and Statistics course for a few years now. This text focuses on research methods, so I do use another text to cover statistical information. I do highly recommend this text for research methods. It is comprehensive, clear, and easy for students to use.

Reviewed by William Johnson, Lecturer, Old Dominion University on 1/12/24

This textbook covers every topic that I teach in my Research Methods course aside from psychology careers (which I would not really expect it to cover). read more

This textbook covers every topic that I teach in my Research Methods course aside from psychology careers (which I would not really expect it to cover).

I have not noticed any inaccurate information (other than directed students to read Malcolm Gladwell). I appreciate that the textbook includes information on research errors that have not been supported by replication efforts, such as embodied cognition.

Many of the basic concepts of research methods are rather timeless, but I appreciate that the text includes newer research as examples while also including "classic" studies that exemplify different methods.

The writing is clear and simple. The keywords are bolded and reveal a definition when clicked, which students often find very helpful. Many of the figures are very helpful in helping students understand various methods (I really like the ones in the single-subject design subchapter).

The book is very consistent in its terminology and writing style, which I see as a positive compared to other open psychology textbooks where each chapter is written by subject matter experts (such as the NOBA intro textbook).

Modularity rating: 4

I teach this textbook almost entirely in order (except for moving chapters 12 & 13 earlier in the semester to aid students in writing Results sections in their final papers). I think that the organization and consistency of the book reduces its modularity, in that earlier chapters are genuinely helpful for later chapters.

Organization/Structure/Flow rating: 4

I preferred the organization of previous editions, which had "Theory in Research" as its own chapter. If I were organizing the textbook, I am not sure that I would have out descriptive or inferential statistics as the final two chapters (I would have likely put Chapter 11: Presenting Your Research as the final chapter). I also would not have put information about replicability and open science in the inferential statistics section.

The text is easy to read and the formatting is attractive. My only minor complaint is that some of the longer subchapters can be a pretty long scroll, but I understand the desire for their only to be one page per subchapter/topic.

I have not noticed any grammatical errors.

Cultural Relevance rating: 3

I do not think the textbook is insensitive, but there is not much thought given to adapting research instruments across cultures. For instance, talking about how different constructs might have different underlying distributions in different cultures would be useful for students. In the survey methods section, a discussion of back translation or emic personality trait measurement/development for example might be a nice addition.

I choose to use this textbook in my methods classes, but I do miss the organization of the previous American editions. Overall, I recommend this textbook to my colleagues.

Reviewed by Brianna Ewert, Psychology Instructor, Salish Kootenai College on 12/30/22

This text includes the majority of content included in our undergraduate Research Methods in Psychology course. The glossary provides concise definitions of key terms. This text includes most of the background knowledge we expect our students to... read more

Comprehensiveness rating: 4 see less

The content I have read is accurate and error-free.

The content is relevant and up-to-date.

The text is clear and concise. I find it pleasantly readable and anticipate undergraduate students will find it readable and understandable as well.

The terminology appears to be consistent throughout the text.

The modular sections stand alone and lend themselves to alignment with the syllabus of a particular course. I anticipate readily selecting relevant modules to assign in my course.

The book is logically organized with clear and section headings and subheadings. Content on a particular topic is easy to locate.

The text is easy to navigate and the format/design are clean and clear. There are not interface issues, distortions or distracting format in the pdf or online versions.

The text is grammatically correct.

Cultural Relevance rating: 4

I have not found culturally insensitive and offensive language or content in the text. For my courses, I would add examples and supplemental materials that are relevant for students at a Tribal College.

This textbook includes supplemental instructor materials, included slides and worksheets. I plan to adopt this text this year in our Research Methods in Psychology course. I expect it to be a benefit to the course and students.

Reviewed by Sara Peters, Associate Professor of Psychology, Newberry College on 11/3/22

This text serves as an excellent resource for introducing survey research methods topics to undergraduate students. It begins with a background of the science of psychology, the scientific method, and research ethics, before moving into the main types of research. This text covers experimental, non-experimental, survey, and quasi-experimental approaches, among others. It extends to factorial and single subject research, and within each topic is a subset (such as observational research, field studies, etc.) depending on the section.

I could find no accuracy issues with the text, and appreciated the discussions of research and cited studies.

There are revised editions of this textbook (this being the 4th), and the examples are up to date and clear. The inclusion of exercises at the end of each chapter offer potential for students to continue working with material in meaningful ways as they move through the book and (and course).

The prose for this text is well aimed at the undergraduate population. This book can easily be utilized for freshman/sophomore level students. It introduces the scientific terminology surrounding research methods and experimental design in a clear way, and the authors provide extensive examples of different studies and applications.

Terminology is consistent throughout the text. Aligns well with other research methods and statistics sources, so the vocabulary is transferrable beyond the text itself.

Navigating this book is a breeze. There are 13 chapters, and each have subsections that can be assigned. Within each chapter subsection, there is a set of learning objectives, and paragraphs are mixed in with tables and figures for students to have different visuals. Different application assignments within each chapter are highlighted with boxes, so students can think more deeply given a set of constructs as they consider different information. The last subsection in each chapter has key summaries and exercises.

The sections and topics in this text are very straightforward. The authors begin with an introduction of psychology as a science, and move into the scientific method, research ethics, and psychological measurement. They then present multiple different research methodologies that are well known and heavily utilized within the social sciences, before concluding with information on how to present your research, and also analyze your data. The text even provides links throughout to other free resources for a reader.

This book can be navigated either online (using a drop-down menu), or as a pdf download, so students can have an electronic copy if needed. All pictures and text display properly on screen, with no distortions. Very easy to use.

There were no grammatical errors, and nothing distracting within the text.

This book includes inclusive material in the discussion of research ethics, as well as when giving examples of the different types of research approaches. While there is always room for improvement in terms of examples, I was satisfied with the breadth of research the authors presented.

This text provides an overview of both research methods, and a nice introduction to statistics for a social science student. It would be a good choice for a survey research methods class, and if looking to change a statistics class into an open resource class, could also serve as a great resource.

Reviewed by Sharlene Fedorowicz, Adjunct Professor, Bridgewater State University on 6/23/21

The comprehensiveness of this book was appropriate for an introductory undergraduate psychology course. Critical topics are covered that are necessary for psychology students to obtain foundational learning concepts for research. Sections within the text and each chapter provide areas for class discussion with students to dive deeper into key concepts for better learning comprehension. The text covered APA format along with examples of research studies to supplement the learning. The text segues appropriately by introducing the science of psychology, followed by scientific method and ethics before getting into the core of scientific research in the field of psychology. Details are provided in quantitative and qualitative research, correlations, surveys, and research design. Overall, the text is fully comprehensive and necessary introductory research concepts.

The text appears to be accurate with no issues related to content.

Relevance/Longevity rating: 4

The text provided relevant research information to support the learning. The content was up-to-date with a variety of different examples related to the different fields of psychology. However, some topics such as in the pseudoscience section were not very relevant and bordered the line of beliefs. Here, more current or relevant solid examples would provide more relevancy in this part of the text. Bringing in more solid or concrete examples that are more current for students may have been more appropriate such as lack of connection between information found on social media versus real science.

The language and flow of the chapters accompanied by the terms, concepts, and examples of applied research allows for clarity of learning content. Terms were introduced at the appropriate time with the support of concepts and current or classic research. The writing style flows nicely and segues easily from concept to concept. The text is easy for students to understand and grasp the details related to psychological research and science.

The text provides consistency in the outline of each chapter. The beginning section chapter starts objectives as an overview to help students unpack the learning content. Key terms are consistently bolded followed by concept or definition and relevant examples. Research examples are pertinent and provide students with an opportunity to understand application of the contents. Practice exercises are provided with in the chapter and at the and in order for students to integrate learning concepts from within the text.

Sections and subsections are clearly organized and divided appropriately for ease-of-use. The topics are easily discernible and follow the flow of ideal learning routines for students. The sections and subsections are consistently outlined for each concept module. The modularity provides consistency allowing for students to focus on content rather than trying to discern how to pull out the information differently from each chapter or section. In addition, each section and subsection allow for flexibility in learning or expanding concepts within the content area.

The organization of the textbook was easy to follow and each major topic was outlined clearly. However, the chapter on presenting research may be more appropriately placed toward the end of the book rather than in the middle of the chapters related to research and research design. In addition, more information could have been provided upfront around APA format so that students could identify the format of citations within the text as practice for students throughout the book.

The interface of the book lends itself to a nice layout with appropriate examples and links to break up the different sections in the chapters. Examples where appropriate and provided engagement opportunities for the students for each learning module. Images and QR codes or easily viewed and used. Key terms are highlighted in relevant figures, graphs, and tables were appropriately placed. Overall, the interface of the text assisted with the organization and flow of learning material.

No grammatical errors were detected in this book.

The text appears to be culturally sensitive and not offensive. A variety of current and classic research examples are relevant. However, more examples of research from women, minorities, and ethnicities would strengthen the culture of this textbook. Instructors may need to supplement some research in this area to provide additional inclusivity.

Overall, I was impressed by the layout of the textbook and the ease of use. The layout provides a set of expectations for students related to the routine of how the book is laid out and how students will be able to unpack the information. Research examples were relevant, although I see areas where I will supplement information. The book provides opportunities for students to dive deeper into the learning and have rich conversations in the classroom. I plan to start using the psychology textbook for my students starting next year.

Reviewed by Anna Behler, Assistant Professo, North Carolina State University on 6/1/21

The text is very thorough and covers all of the necessary topics for an undergraduate psychology research methods course. There is even coverage of qualitative research, case studies, and the replication crisis which I have not seen in some other... read more

There were no issues with the accuracy of the text.

The content is very up to date and relevant for a research methods course. The only updates that will likely be necessary in the coming years are updates to examples and modifications to the section on APA formatting.

The clarity of the writing was good, and the chapters were written in a way that was accessible and easy to follow.

I did not note any issues with consistency.

Each chapter is divided into multiple subsections. This makes the chapters even easier to read, as they are broken down into short and easy to navigate sections. These sections make it easy to assign readings as needed depending on which topics are being covered in class.

Organization/Structure/Flow rating: 3

The organization was one of the few areas of weakness, and I felt that the chapters were ordered somewhat oddly. However, this is something that is easily fixed, as chapters (and even subsections) can be assigned in whatever order is needed.

There were no issues of note with the interface, and the PDF of the text was easy to navigate.

The text was well written and there were no grammatical/writing errors of note.

Overall, the book did not contain any notable instances of bias. However, it would probably be appropriate to offer a more thorough discussion of the WEIRD problem in psychology research.

Reviewed by Seth Surgan, Professor, Worcester State University on 5/24/21

Pitched very well for a 200-level Research Methods course. This text provided students with solid basis for class discussion and the further development of their understanding of fundamental concepts. read more

No issues with accuracy.

Coverage was on target, relevant, and applicable, with good examples from a variety of subfields within Psychology.

Clearly written -- students often struggle with the dry, technical nature of concepts in Research Methods. Part of the reason I chose this text in the first place was how favorably it compared to other options in terms of clarity.

No problems with inconsistent of shifting language. This is extremely important in Research Methods, where there are many closely related terms. Language was consistent and compatible with other textbook options that were available to my students.

Chapters are broken down into sections that are reasonably sized and conceptually appropriate.

The organization of this textbook fit perfectly with the syllabus I've been using (in one form or another) for 15+ years.

This textbook was easy to navigate and available in a variety of formats.

No problems at all.

Examples show an eye toward inclusivity. I did not detect any insensitive or offensive examples or undertones.

I have used this textbook for a 200-level Research Methods course run over a single summer session. This was my first experience using an OER textbook and I don't plan on going back.

Reviewed by Laura Getz, Assistant Professor, University of San Diego on 4/29/21

The topics covered seemed to be at an appropriate level for beginner undergraduate psychology students; the learning objectives for each subsection and the key takeaways and exercises for each chapter are also very helpful in guiding students’ attention to what is most relevant. The glossary is also thorough and a good resource for clear definitions. I would like to see a final chapter on a “big picture” or integrating key ideas of replication, meta-analysis, and open science.

Content Accuracy rating: 4

For the most part, I like the way information is presented. I had a few specific issues with definitions for ordinal variables being quantitative (1st, 2nd, 3rd aren’t really numbers as much as ranked categories), the lack of specificity about different forms of validity (face, content, criterion, and discriminant all just labeled “validity” whereas internal and external validity appear in different sections), and the lack of clear distinction between correlational and quasi-experimental variables (e.g., in some places, country of origin is listed as making a design quasi-experimental, but in other chapters it is defined as correlational).

Some of the specific studies/experiments mentioned do not seem like the best or most relevant for students to learn about the topics, but for the most part, content is up-to-date and can definitely be updated with new studies to illustrate concepts with relative ease.

Besides the few concepts I listed above in “accuracy”, I feel the text was very accessible, provides clear definitions, and many examples to illustrate any potential technical/jargon terms.

I did not notice any issues with inconsistent terms except for terms that do have more than one way of describing the same concept (e.g., 2-sample vs. independent samples t-test)

I assigned the chapters out of order with relative ease, and students did not comment about it being burdensome to navigate.

The order of chapters sometimes did not make sense to me (e.g., Experimental before Non-experimental designs, Quasi-experimental designs separate from other non-experimental designs, waiting until Chapter 11 to talk about writing), but for the most part, the chapter subsections were logical and clear.

Interface rating: 4

I had no issues navigating the online version of the textbook other than taking a while to figure out how to move forward and back within the text itself rather than going back to the table of contents (this might just be a browser issue, but is still worth considering).

No grammatical errors of note.

There was nothing explicitly insensitive or offensive about the text, but there were many places where I felt like more focus on diversity and individual differences could be helpful. For example, ethics and history of psychological testing would definitely be a place to bring in issues of systemic racism and/or sexism and a focus on WEIRD samples (which is mentioned briefly at another point).

I was very satisfied with this free resource overall, and I recommend it for beginning level undergraduate psychology research methods courses.

Reviewed by Laura Stull, Associate Professor, Anderson University on 4/23/21

This book covers essential topics and areas related to conducting introductory psychological research. It covers all critical topics, including the scientific method, research ethics, research designs, and basic descriptive and inferential statistics. It even goes beyond other texts in terms of offering specific guidance in areas like how to conduct research literature searches and psychological measurement development. The only area that appears slightly lacking is detailed guidance in the mechanics of writing in APA style (though excellent basic information is provided in chapter 11).

All content appears accurate. For example, experimental designs discussed, descriptive and inferential statistical guidance, and critical ethical issues are all accurately addressed, See comment on relevance below regarding some outdated information.

Relevance/Longevity rating: 3

Chapter 11 on APA style does not appear to cover the most current version of the APA style guide (7th edition). While much of the information in Chapter 11 is still current, there are specifics that did change from 6th to 7th edition of the APA manual and so, in order to be current, this information would have to be supplemented with external sources.

The book is extremely well organized, written in language and terms that should be easily understood by undergraduate freshmen, and explains all necessary technical jargon.

The text is consistent throughout in terms of terminology and the organizational framework (which aids in the readability of the text).

The text is divided into intuitive and common units based on basic psychological research methodology. It is clear and easy to follow and is divided in a way that would allow omission of some information if necessary (such as "single subject research") or reorganization of information (such as presenting survey research before experimental research) without disruption to the course as a whole.

As stated previously, the book is organized in a clear and logical fashion. Not only are the chapters presented in a logical order (starting with basic and critical information like overviews of the scientific method and research ethics and progressing to more complex topics like statistical analyses).

No issues with interface were noted. Helpful images/charts/web resources (e.g., Youtube videos) are embedded throughout and are even easy to follow in a print version of the text.

No grammatical issues were noted.

No issues with cultural bias are noted. Examples are included that address topics that are culturally sensitive in nature.

I ordered a print version of the text so that I could also view it as students would who prefer a print version. I am extremely impressed with what is offered. It covers all of the key content that I am currently covering with a (non-open source) textbook in an introduction to research methods course. The only concern I have is that APA style is not completely current and would need to be supplemented with a style guide. However, I consider this a minimal issue given all of the many strengths of the book.

Reviewed by Anika Gearhart, Instructor (TT), Leeward Community College on 4/22/21

Includes the majority of elements you expect from a textbook covering research methods. Some topics that could have been covered in a bit more depth were factorial research designs (no coverage of 3 or more independent variables) and external... read more

Nothing found that was inaccurate.

Looks like a few updates could be made to chapter 11 to bring it up to date with APA 7. Otherwise, most examples are current.

Very clear, a great fit for those very new to the topic.

The framework is clear and logical, and the learning objectives are very helpful for orienting the reader immediately to the main goals of each section.

Subsections are well-organized and clear. Titles for sections and subsections are clear.

Though I think the flow of this textbook for the most part is excellent, I would make two changes: move chapter 5 down with the other chapters on experimental research and move chapter 11 to the very end. I feel that this would allow for a more logical presentation of content.

The webpage navigation is easy to use and intuitive, the ebook download works as designed, and the page can be embedded directly into a variety of LMS sites or used with a variety of devices.

I found no grammatical errors in this book.

While there were some examples of studies that included participants from several cultures, the book does not touch on ecological validity, an important external validity issue tied to cultural psychology, and there is no mention of the WEIRD culture issue in psychology, which seems somewhat necessary when orienting new psychology students to research methods today.

I currently use and enjoy this textbook in my research methods class. Overall, it has been a great addition to the course, and I am easily able to supplement any areas that I feel aren't covered with enough breadth.

Reviewed by Amy Foley, Instructor/Field & Clinical Placement Coordinator, University of Indianapolis on 3/11/21

This text provides a comprehensive overview of the research process from ideation to proposal. It covers research designs common to psychology and related fields. read more

This text provides a comprehensive overview of the research process from ideation to proposal. It covers research designs common to psychology and related fields.

Accurate information!

This book is current and lines up well with the music therapy research course I teach as a supplemental text for students to understand research designs.

Clear language for psychology and related fields.

The format of the text is consistent. I appreciate the examples, different colored boxes, questions, and links to external sources such as video clips.

It is easy to navigate this text by chapters and smaller units within each chapter. The only confusion that has come from using this text includes the fact that the larger units have roman numerals and the individual chapters have numbers. I have told students to "read unit six" and they only read the small chapter 6, not the entire unit for example.

Flows well!

I have not experienced any interface issues.

I have not found any grammar errors.

Book appears culturally relevant.

This is a great resource for research methods courses in psychology or related fields. I am glad to have used several chapters of this text within the music therapy research course I teach where students learn about research design and then create their own research proposal.

Reviewed by Veronica Howard, Associate Professor, University of Alaska Anchorage on 1/11/21, updated 1/11/21

VERY impressed by the coverage of single subject designs. I would recommend this content to colleagues. read more

VERY impressed by the coverage of single subject designs. I would recommend this content to colleagues.

Content appears accurate.

By expanding to include more contemporary research perspectives, the authors have created a wonderful dynamic that permits the text to be the foundation for many courses as well as revision and remixing for other authors.

Book easy to read, follow.

Consistency rating: 4

Content overall consistent. Only mild inconsistency in writing style between chapters.

Exceptionally modular. All content neatly divided into units with smaller portions. This would be a great book to use in a course that meets bi-weekly, or adapted into other formats.

Content organized in a clear and logical fashion, and would guide students through a semester-long course on research methods, starting with review content, broad overview of procedures (including limitations), then highlighting less common (though relevant) procedures.

Rich variety of formats for use.

No errors found.

I would appreciate more cultural examples.

Reviewed by Greg Mullin, Associate Professor, Bunker Hill Community College on 12/30/20, updated 1/6/21

I was VERY pleased with the comprehensiveness of the text. I believe it actually has an edge over the publisher-based text that I've been using for years. Each major topic was thoroughly covered with more than enough detail on individual concepts. read more

I did not find any errors within the text. The authors provided an unbiased representation of research methods in psychology.

The content connects to classic, timeless examples in the field, but also mixes in a fair amount of more current, relatable examples. I feel like I'll be able to use this version of the text for many years without its age showing.

The authors present a clear and efficient writing style throughout that is rich with relatable examples. The only area that may be a bit much for undergraduate-level student understanding is the topic of statistics. I personally scale back my discussion of statistics in my Intro to Research Methods course, but for those that prefer a deeper dive, the higher-level elements are there.

I did not notice any shifts with the use of terminology or with the structural framework of the text. The text is very consistent and organized in an easily digestible way.

The authors do a fantastic job breaking complex topics down into manageable chunks both as a whole and within chapters. As I was reading, I could easily see how I could align my current approach of teaching Intro to Research Methods with their modulated presentation of the material.

I effortlessly moved through the text given the structural organization. All topics are presented in a logical fashion that allowed each message to be delivered to the reader with ease.

I read the text through the PDF version and found no issue with the interface. All image and text-based material was presented clearly.

I cannot recall coming across any grammatical errors. The text is very well written.

I did not find the text to be culturally insensitive in any way. The authors use inclusive language and even encourage that style of writing in the chapter on Presenting Your Research. I would have liked to see more cross-cultural research examples and more of an extended effort to include the theme of diversity throughout, but at no point did I find the text to be offensive.

This is a fantastic text and I look forward to adopting it for my Intro to Research Methods course in the Spring. :)

Reviewed by Maureen O'Connell, Adjunct Professor, Bunker Hill Community College on 12/15/20, updated 12/18/20

This text edition has covered all ideas and areas of research methods in psychology. It has provided a glossary of terms, sample APA format, and sample research papers. read more

This text edition has covered all ideas and areas of research methods in psychology. It has provided a glossary of terms, sample APA format, and sample research papers.

The content is unbiased, accurate, and I did not find any errors in the text.

The content is current and up-to-date. I found that the text can be added to should material change, the arrangement of the text/content makes it easily accessible to add material, if necessary.

The text is clear, easy to understand, simplistic writing at times, but I find this text easy for students to comprehend. All text is relevant to the content of behavioral research.

The text and terminology is consistent.

The text is organized well and sectioned appropriately. The information is presented in an easy-to-read format, with sections that can be assigned at various points during the semester and the reader can easily locate this.

The topics in the text are organized in a logical and clear manner. It flows really well.

The text is presented well, including charts, diagrams, and images. There did not appear to be any confusion with this text.

The text contains no grammatical errors.

The text was culturally appropriate and not offensive. Clear examples of potential biases were outlined in this text which I found quite helpful for the reader.

Overall, I found this to be a great edition. Much of the time I spend researching outside material for students has been included in this text. I enjoyed the format, easier to navigate, helpful to students by providing an updated version of discussions and practice assignments, and visually more appealing.

Reviewed by Brittany Jeye, Assistant Professor of Psychology, Worcester State University on 6/26/20

All of the main topics in a Research Methods course are covered in this textbook (e.g., scientific method, ethics, measurement, experimental design, hypothesis testing, APA style, etc.). Some of these topics are not covered as in-depth as in other Research Method textbooks I have used previously, but this actually may be a positive depending on the students and course level (that is, students may only need a solid overview of certain topics without getting overwhelmed with too many details). It also gives the instructor the ability to add content as needed, which helps with flexibility in course design.

I did not note any errors or inaccurate/biasing statements in the text.

For the most part, everything was up to date. There was a good mix of classic research and newer studies presented and/or used as examples, which kept the chapters interesting, topical and relevant. I only noted the section on APA Style in the chapter “Presenting Your Research” which may need some updating to be in line with the new APA 7th edition. However, there should be only minor edits needed (the chapter itself was great overview and introduction to the main points of APA style) and it looks like they should be relatively easy to implement.

The text was very well-written and was presented at an accessible level for undergraduates new to Research Methods. Terms were well-defined with a helpful glossary at the end of the textbook.

The consistent structure of the textbook is huge positive. Each chapter begins with learning objectives and ends with bulleted key takeaways. There are also good exercises and learning activities for students at the end of each chapter. Instructors may need to add their own activities for chapters that do not go into a lot of depth (there are also instructor resources online, which may have more options available).

This is one of the biggest strengths of this textbook, in my opinion. I appreciate how each chapter is broken down into clearly defined subsections. The chapters and the subsections, in particular, are not lengthy, which is great for students’ learning. These subsections could be reorganized and used in a variety of ways to suit the needs of a particular course (or even as standalone subsections).

The topics were presented in a logical manner. As mentioned above, since the textbook is very modular, I feel that you could easily rearrange the chapters to fit your needs (for example, presenting survey design before experimental research or making the presenting your research section a standalone unit).

I downloaded the textbook as an ebook, which was very easy to use/navigate. There were no problems reading any of the text or figures/tables. I also appreciated that you could open the ebook using a variety of apps (Kindle, iBook, etc.) depending on your preference (and this is good for students who have a variety of technical needs).

There were no grammatical errors noted.

The examples were inclusive of races, ethnicity and background and there were not any examples that were culturally insensitive or offensive in any way. In future iterations of the replicability section, it may be beneficial to touch upon the “weird” phenomena in psychology research (that many studies use participants who are western, educated and from industrialized, rich and democratic countries) as a point to engage students in improving psychological practices.

I will definitely consider switching to this textbook in the future for Research Methods.

Reviewed by Alice Frye, Associate Teaching Professor, University of Massachusetts Lowell on 6/22/20

Hits all the necessary marks from ways of knowing to measurement, research designs, and presentation. Comparable in detail and content to other Research Methods texts I have used for teaching. read more

Hits all the necessary marks from ways of knowing to measurement, research designs, and presentation. Comparable in detail and content to other Research Methods texts I have used for teaching.

Correct and to the point. Complex ideas such as internal consistency reliability and discriminant validity are well handled--correct descriptions that are also succinct and articulated simply and with clear examples that are easy for a student reader to grasp.

Seems likely to have good staying power. One area that has changed quickly in the past is the usefulness of various research data bases. So it is possible that portion could become more quickly outdated, but there is no predicting that. The current descriptions are useful.

Very clearly written without being condescending, overly casual or clunky.

Excellent consistency throughout in terms of organization, language usage, level of detail and tone.

Imho this is one of the particular strengths of the text. Chapters are well divided into discrete parts, which seems likely to be a benefit in cohorts of students who are increasingly accustomed to digesting small amounts of information.

Well organized, straightforward structure that is maintained throughout.

No problems with the interface.

The grammar level is another notable strength. Ideas are articulated clearly, and with sophistication, but in a syntactically very straightforward manner.

The text isn't biased or offensive. I wish that to illustrate various points and research designs it had drawn more frequently on research studies that incorporate a specific focus on race and ethnicity.

This is a very good text. As good as any for profit text I have used to teach a research methods course, if not better.

Reviewed by Lauren Mathieu-Frasier, Adjunct Instructor, University of Indianapolis on 1/13/20

As other reviews have mentioned, this textbook provides a comprehensive look at multiple concepts for an introductory course in research methods in psychology. Some of the concepts (i.e., variables, external validity) are briefly described and glossed over that it will take additional information, examples, and reinforcement from instructors in the classroom. Other sections and concepts, like ethics or reporting of research were well-described and thorough.

It appeared that the information was accurate, error-free, and unbiased.

The information is up-to-date. In the section on APA presentation, it looks like the minor adjustments to the APA Publication Manual 7th Edition would need to be included. However, this section gives a good foundation and the instructor can easily implement the changes.

Clarity rating: 4

The text is clearly written written and provides an appropriate context when terminology is used.

There aren't any issues with consistency in the textbook.

The division of smaller sections can be beneficial when reading it and assigning it to classes. The sections are clearly organized based on learning objectives.

The textbook is organized in a logical, clear manner. There may be topics that instructors choose to present in a different manner (non-experimental and survey research prior to experimental). However, this doesn't generally impact the organization and flow of the book.

While reading and utilizing the book, there weren't any navigation issues that could impact the readability of the book. Students could find this textbook easy to use.

Grammatical errors were not noted.

There weren't any issues with cultural sensitivity in the examples of studies used in the textbook.

Reviewed by Tiffany Kindratt, Assistant Professor, University of Texas at Arlington on 1/1/20

The text is comprehensive with an effective glossary of terms at the end. It would be beneficial to include additional examples and exercises for students to better understand concepts covered in Chapter II, Overview of the Scientific Method,... read more

The text is accurate and there are minimal type/grammatical errors throughout. The verbiage is written in an unbiased manner consistently throughout the textbook.

The content is up-to-date, and examples can be easily updated for future versions. As a public health instructor, I would be interested in seeing examples of community-based examples in future versions. The current examples provided are relevant for undergraduate public health students as well as psychology students.

The text is written in a clear manner. The studies used can be easily understood by undergraduate students in other social science fields, such as public health. More examples and exercises using inferential statistics would be helpful for students to better grasp the concepts.

The framework for each chapter and terminology used are consistent. It is helpful that each section within each chapter begins with learning objectives and the chapter ends with key takeaways and exercises.

The text is clearly divided into sections within each chapter. When I first started reviewing this textbook, I thought each section was actually a very short chapter. I would recommend including a listing of all of the objectives covered in each chapter at the beginning to improve the modularity of the text.

Some of the topics do not follow a logical order. For example, it would be more appropriate to discuss ethics before providing the overview of the scientific method. It would be better to discuss statistics used to determine results before describing how to write manuscripts. However, the text is written in a way that that the chapters could be assigned to students in a different order without impacting the students’ comprehension of the concepts.

I did not encounter any interface issues when reviewing this text. All links worked and there were no distortions of the images or charts that may confuse the reader. There are several data tables throughout the text which are left-aligned and there is a large amount of empty white space next it. I would rearrange the text in future versions to make better use of this space.

The text contains minimal grammatical errors.

The examples are culturally relevant. I did not see any examples that may be considered culturally insensitive or offensive in any way.

As an instructor for an undergraduate public health sciences and methods course, I will consider using some of the content in this text to supplement the current textbook in the future.

Reviewed by Mickey White, Assistant Professor, East Tennessee State University on 10/23/19

The table of contents is well-formatted and comprehensive. Easy to navigate and find exactly what is needed, students would be able to quickly find needed subjects. read more

The table of contents is well-formatted and comprehensive. Easy to navigate and find exactly what is needed, students would be able to quickly find needed subjects.

Content appears to be accurate and up-to-date.

This text is useful and relevant, particularly with regard to expressing and reporting descriptive statistics and results. As APA updates, the text will be easy to edit, as the sections are separated.

Easy to read and engaging.

Chapters were laid out in a consistent manner, which allows readers to know what is coming. The subsections contained a brief overview and terminology was consistent throughout. The glossary added additional information.

Sections and subsections are delineated in a usable format.

The key takeaways were useful, including the exercises at the end of each chapter.

Reading the book online is a little difficult to navigate page-by-page, but e-pub and PDF formats are easy to navigate.

No errors noted.

Would be helpful to have a clearer exploration of cultural factors impacting research, including historical bias in assessment and research outside of research ethics.

Reviewed by Robert Michael, Assistant Professor, University of Louisiana at Lafayette on 10/14/19

Successfully spans the gamut of topics expected in a Research Methods textbook. Some topics are covered in-depth, while others are addressed only at a surface level. Instructors may therefore need to carefully arrange class material for topics in... read more

The factual content was error-free, according to my reading. I did spot a few grammatical and typographical errors, but they were infrequent and minor.

Great to see nuanced—although limited—discussion of issues with Null Hypothesis Significance Testing, Reproducibility in Psychological Science, and so forth. I expect that these areas are likely to grow in future editions, perhaps supplementing or even replacing more traditional material.

Extremely easy to read with multiple examples throughout to illustrate the principles being covered. Many of these examples are "classics" that students can easily relate to. Plus, who doesn't like XKCD comics?

The textbook is structured sensibly. At times, certain authors' "voices" seemed apparent in the writing, but I suspect this variability is unlikely to be noticed by or even bothersome to the vast majority of readers.

The topics are easily divisible and seem to follow routine expectations. Instructors might find it beneficial and/or necessary to incorporate some of the statistical thinking and learning into various earlier chapters to facilitate student understanding in-the-moment, rather than trying to leave all the statistics to the end.

Sensible and easy-to-follow structure. As per "Modularity", the Statistical sections may benefit from instructors folding in such learning throughout, rather than only at the end.

Beautifully presented, crisp, easy-to-read and navigate. Caveat: I read this online, in a web-browser, on only one device. I haven't tested across multiple platforms.

High quality writing throughout. Only a few minor slip-ups that could be easily fixed.

Includes limited culturally relevant material where appropriate.

Reviewed by Matthew DeCarlo, Assistant Professor, Radford University on 6/26/19

The authors do a great job of simplifying the concepts of research methods and presenting them in a way that is understandable. There is a tradeoff between brevity and depth here. Faculty who adopt this textbook may need to spend more time in class going in depth into concepts, rather than relying on the textbook for all of the information related to key concepts. The text does not cover qualitative methods in detail.

The textbook provides an accurate picture of research methods. The tone is objective and without bias.

The textbook is highly relevant and up to date. Examples are drawn from modern theories and articles.

The writing is a fantastic mix of objective and authoritative while also being approachable.

The book coheres well together. Each chapter and section are uniform.

This book fits very well within a traditional 16 week semester, covering roughly a chapter per week. One could take out specific chapters and assign them individually if research methods is taught in a different way from a standard research textbook.

Content is very well organized. The table of contents is easy to navigate and each chapter is presented in a clear and consistent manner. The use of a two-tier table of contents is particularly helpful.

Standard pressbooks interface, which is great. Uses all of the standard components of Pressbooks well, though the lack of H5P and interactive content is a drawback.

I did not notice any grammar errors.

Cultural Relevance rating: 2

The book does not deal with cultural competence and humility in the research process. Integration of action research and decolonization perspectives would be helpful.

Reviewed by Christopher Garris, Associate Professor, Metropolitan State University of Denver on 5/24/19

Most content areas in this textbook were covered appropriately extensively. Notably, this textbook included some content that is commonly missing in other textbooks (e.g. presenting your research). There were some areas where more elaboration and more examples were needed. For example, the section covering measurement validities included all the important concepts, but needed more guidance for student comprehension. Also, the beginning chapters on 'common sense' reasoning and pseudoscience seemed a little too brief.

Overall, this textbook appeared to be free from glaring errors. There were a couple of instances of concern, but were not errors, per se. For example, the cut-off for Cronbach's alpha was stated definitively at .80, while this value likely would be debated among researchers.

This textbook was presented in such a way that seemed protect it from becoming obsolete within the next few years. This is important for continued, consistent use of the book. The authors have revised this book, and those revisions are clearly summarized in the text. Importantly, the APA section of the textbook appears to be up-to-date. Also, the use of QR codes throughout the text is a nice touch that students may appreciate.

Connected to comprehensiveness, there are some important content areas that I felt were lacking in elaboration and examples (e.g. testing the validity of measurement; introduction of experimental design), which inhibits clarity. Overall, however, the topics seemed to be presented in a straightforward, accessible manner. The textbook includes links to informative videos and walk-throughs where appropriate, which seem to be potentially beneficial for student comprehension. The textbook includes tools designed to aid learning, namely "Key Takeaways" and "Exercises" sections at the end of most modules, but not all. "Key Takeaways" seemed valuable, as they were a nice bookend to the learning objectives stated at the beginning of each module. "Exercises" did not appear to be as valuable, especially for the less-motivated student. On their face, these seemed to be more designed for instructors to use as class activities/active learning. Lastly, many modules of the textbook were text-heavy and visually unappealing. While this is superficial, the inclusion of additional graphics, example boxes, or figures in these text-heavy modules might be beneficial.

The textbook appeared to be internally consistent with its approach and use of terminology.

The textbook had a tendency to 'throw out' big concepts very briefly in earlier modules (e.g. sampling, experimental/non-experimental design), and then cover them in more detail in later modules. This would have been less problematic if the text would explicitly inform the student that these concepts would be elaborated upon later. Beyond this issue, the textbook seems to lend itself to being divided up and used on module-by-module basis.

The organization of the chapters did not make intuitive sense to me. The fact that correlation followed experimental research, and that descriptive research was the second-to-last module in the sequence was confusing. That said, textbook is written in such a way that an instructor easily assign the modules in the order that works best for their class.

Overall, the interface worked smoothly and there were few technical issues. Where there were issues (e.g. inconsistent spacing between lines and words), they were negligible.

The text seemed to be free from glaring grammatical problems.

Because this is a methodology textbook, it does not lend itself to too much cultural criticism. That said, the book did not rely on overly controversial examples, but also didn't shy away from important cultural topics (e.g. gender stereotypes, vaccines).

Reviewed by Michel Heijnen, Assistant Professor, University of North Carolina Wilmington on 3/27/18

The book covers all areas related to research methods, not only for the field of psychology, but also to other related fields like exercise science. Topics include ethics, developing a research questions, experimental designs, non-experimental... read more

Reviewed content is accurate and seems free of any personal bias.

The topic of research methods in general is not expected to change quickly. It is not expected that this text will become obsolete in the near future. Furthermore, for both the field of psychology as well as other related fields, the examples will continue to have an application to explain certain concepts and will not be outdated soon, even with new research emerging every day.

The text is written so an undergraduate student should be able to understand the concepts. The examples provided in the text greatly contribute to the understanding of the topics and the proposed exercises at the end of each chapter will further apply the knowledge.

The layout and writing style are consistent throughout the text.

Layout of the text is clear, with multiple subsection within each chapter. Each chapter can easily be split into multiple subsection to assign to students. No evidence of self-refers was observed, and individual chapters could be assigned to students without needed to read all preceding chapters. For example, Chapter 4 may not be particularly useful to students outside of psychology, but an instructor can easily reorganize the text and skip this chapter while students can still understand following chapters.

Topics are addressed in a logical manner. Overall, an introduction to research is provided first (including ethics to research), which is followed by different types of research, and concludes with types of analysis.

No images or tables are distorted, making the text easy to read.

No grammatical errors observed in text.

Text is not offensive and does not appear to be culturally insensitive.

I believe that this book is a great resource and, as mentioned previously, can be used for a wider audience than just psychology as the basics of research methods can be applied to various fields, including exercise science.

Reviewed by Chris Koch, Professor of Psychology, George Fox University on 3/27/18

All appropriate areas and topics are covered in the text. In that sense, this book is equivalent to other top texts dealing with research methods in psychology. The appeal of this book is the brevity and clarity. Therefore, some may find that, although the topics are covered, topics may not be covered as thoroughly they might like. Overall, the coverage is solid for an introductory course in research methods.

In terms of presentation, this book could be more comprehensive. Each chapter does start with a set of learning objectives and ends with "takeaways" and a short set of exercises. However, it lacks detailed chapter outlines, summaries, and glossaries. Furthermore, an index does not accompany the text.

I found the book to be accurate with content being fairly presented. There was no underlying bias throughout the book.

This is an introductory text for research methods. The basics of research methods have been consistent for some time. The examples used in the text fit the concepts well. Therefore, it should not be quickly dated. It is organized in such a way that sections could be easily modified with more current examples as needed.

The text is easy to read. It is succinct yet engaging. Examples are clear and terminology is adequately defined.

New terms and concepts are dealt with chapter by chapter. However, those things which go across chapters are consistently presented.

The material for each chapter is presented in subsections with each subsection being tied to a particular learning objective. It is possible to use the book by subsection instead of by chapter. In fact, I did that during class by discussing the majority of one chapter, discussing another chapter, and then covering what I previously skipped,

In general, the book follows a "traditional" organization, matching the organization of many competing books. As mentioned in regard to modularity, I did not follow the organization of the book exactly as it was laid out. This may not necessarily reflect poorly on the book, however, since I have never followed the order of any research methods book. My three exams covered chapter 1 through 4, chapters 5, 6, part of 8, and chapters 7, the remainder of 8, 9, and 10. Once we collected data I covered chapters 11 through 13.

Interface rating: 3

The text and images are clear and distortion free. The text is available in several formats including epub, pdf, mobi, odt, and wxr. Unfortunately, the electronic format is not taken full advantage of. The text could be more interactive. As it is, it is just text and images. Therefore, the interface could be improved.

The book appeared to be well written and edited.

I did not find anything in the book that was culturally insensitive or offensive. However, more examples of cross-cultural research could be included.

I was, honestly, surprised by how much I liked the text. The material was presented in easy to follow format that is consistent with how I think about research methods. That made the text extremely easy to use. Students also thought the book was highly accessible Each chapter was relatively short but informative and easy to read.

Reviewed by Kevin White, Assistant Professor, East Carolina University on 2/1/18

This book covers all relevant topics for an introduction to research methods course in the social sciences, including measurement, sampling, basic research design, and ethics. The chapters were long enough to be somewhat comprehensive, but short enough to be digestible for students in an introductory-level class. Student reviews of the book have so far been very positive. The only section of the text for which more detail may be helpful is 2.3 (Reviewing the Research Literature), in which more specific instructions related to literature searches may be helpful to students.

I did not notice any issues related to accuracy. Content appeared to be accurate, error-free, and unbiased.

One advantage of this book is that it is relevant to other applied fields outside of psychology (e.g., social work, counseling, etc.). Also, the exercises at the end of chapter sections are helpful.

The clarity of the text provides students with succinct definitions for research-related concepts, without unnecessary discipline-specific jargon. One suggestion for future editions would be to make the distinctions between different types of non-experimental research a bit more clear for students in introductory classes (e.g., "Correlational Research" in Section 7.2).

Formatting and terminology was consistent throughout this text.

A nice feature of this book is that instructors can select individual sections within chapters, or even jump between sections within chapters. For example, Section 1.4 may not fit for a class that is less clinically-oriented in nature.

The flow of the text was appropriate, with ethics close to the beginning of the book (and an entire chapter devoted to it), and descriptive/inferential statistics at the end.

I did not notice any problems related to interface. I had no trouble accessing or reading the text, and the images were clear.

The text contained no discernible grammatical errors.

The book does not appear to be culturally insensitive in any discernible way, and explicitly addresses prejudice in research (e.g., Section 5.2). However, I think that continuing to add more examples that relate to specific marginalized groups would help improve the text (and especially exercises).

Overall, this book is very useful for an introductory research methods course in psychology or social work, and I highly recommend.

Reviewed by Elizabeth Do, Instructor, Virginia Commonwealth University on 2/1/18

Although this textbook does provide good information regarding introductory concepts necessary for the understanding of correlational designs, and is presented in a logical order. It does not, however, cover qualitative methodologies, or research... read more

There does not seem to be any errors within the text.

Since this textbook covers a topic that is unlikely to change over the years and it's content is up-to-date, it remains relevant to the field.

The textbook is written at an appropriate level for undergraduate students and is useful in that it does explain important terminology.

There does not seem to be any major inconsistencies within the text.

Overall, the text is very well organized - it is separated into chapters that are divided up into modules and within each module, there are clear learning objectives. It is also helpful that the textbook includes useful exercises for students to practice what they've read about from the text.

The topics covered by this textbook are presented in an order that is logical. The writing is clear and the examples are very useful. However, more information could be provided in some of the chapters and it would be useful to include a table of contents that links to the different chapters within the PDF copy, for reader's ease in navigation when looking for specific terms and/or topics.

Overall, the PDF copy of the textbook made it easy to read; however, there did seem to be a few links that were missing. Additionally, it would be helpful to have some of the graphs printed in color to help with ease of following explanations provided by the text. The inclusion of a table of contents would also be useful for greater ease with navigation.

There does not seem to be any grammatical errors in the textbook. Also, the textbook is written in a clear way, and the information flows nicely.

This textbook focuses primarily on examples from the United States. It does not seem to be culturally insensitive or offensive in anyway and I liked that it included content regarding the avoidance of biased language (chapter 11).

This textbook makes the material very accessible, and it is easy to read/follow examples.

Reviewed by Eric Lindsey, Professor, Penn State University Berks Campus on 2/1/18

The content of the Research Methods in Psychology textbook was very thorough and covered what I would consider to be the important concepts and issues pertaining to research methods. I would judge that the textbook has a comparable coverage of information to other textbooks I have reviewed, including the current textbook I am using. The range of scholarly sources included in the textbook was good, with an appropriate balance between older and classic research examples and newer more cutting edge research information. Overall, the textbook provides substantive coverage of the science of conducting research in the field of psychology, supported by good examples, and thoughtful questions.

The textbook adopts a coherent and student-friendly format, and offers a precise introduction to psychological research methodology that includes consideration of a broad range of qualitative and quantitative methods to help students identify and evaluate the best approach for their research needs. The textbook offers a detailed review of the way that psychological researchers approach their craft. The author guides the reader through all aspects of the research process including formulating objectives, choosing research methods, securing research participants, as well as advice on how to effectively collect, analyze and interpret data and disseminate those findings to others through a variety of presentation and publication venues. The textbook offers relevant supplemental information in textboxes that is highly relevant to the material in the accompanying text and should prove helpful to learners. Likewise the graphics and figures that are included are highly relevant and clearly linked to the material presented in the text. The information covered by the textbook reflects an accurate summary of current techniques and methods used in research in the field of psychology. The presentation of information addresses the pros and cons of different research strategies in an objective and evenhanded way.

The range of scholarly sources included in the textbook was good, with an appropriate balance between older, classic research evidence and newer, cutting edge research. Overall, the textbook provides substantive coverage of the science on most topics in research methods of psychology, supported by good case studies, and thoughtful questions. The book is generally up to date, with adequate coverage of basic data collection methods and statistical techniques. Likewise the review of APA style guidelines is reflects the current manual and I like the way the author summarizes changes from the older version of the APA manual. The organization of the textbook does appear to lend itself to editing and adding new information with updates in the future.

I found the textbook chapters to be well written, in a straightforward yet conversational manner. It gives the reader an impression of being taught by a knowledgeable yet approachable expert. The writing style gives the learner a feeling of being guided through the lessons and supported in a very conversational approach. The experience of reading the textbook is less like being taught and more like a colleague sharing information. Furthermore, the style keeps the reader engaged but doesn't detract from its educational purpose. I also appreciate that the writing is appropriately concise. No explanations are so wordy as to overwhelm or lull the reader to sleep, but at the same time the information is not so vague that the reader can't understand the point at all.

The book’s main aim is to enable students to develop their own skills as researchers, so they can generate and advance common knowledge on a variety of psychological topics. The book achieves this objective by introducing its readers, step-by-step, to psychological research design, while maintaining an excellent balance between substance and attention grabbing examples that is uncommon in other research methods textbooks. Its accessible language and easy-to-follow structure and examples lend themselves to encouraging readers to move away from the mere memorization of facts, formulas and techniques towards a more critical evaluation of their own ideas and work – both inside and outside the classroom. The content of the chapters have a very good flow that help the reader to connect information in a progressive manner as they proceed through the textbook.

Each chapter goes into adequate depth in reviewing both past and current research related to the topic that it covers for an undergraduate textbook on research methods in psychology. The information within each chapter flows well from point-to-point, so that the reader comes away feeling like there is a progression in the information presented. The only limitation that I see is that I felt the author could do a little more to let the reader know how information is connected from chapter to chapter. Rather than just drawing the reader’s attention to things that were mentioned in previous chapters, it would be nice to have brief comments about how issues in one chapter relate to topics covered in previous chapters.

In my opinion the chapters are arranged in easily digestible units that are manageable in 30-40 minute reading sessions. In fact, the author designed the chapters of the textbook in a way to make it easy to chunk information, and start and stop to easily pick up where one leaves off from one reading session to another. I also found the flow of information to be appropriate, with chapters containing just the right amount of detail for use in my introductory course in research methods in psychology.

The book is organized into thirteen chapters. The order of the chapters offers a logical progression from a broad overview of information about the principles and theory behind research in psychology, to more specific issues concerning the techniques and mechanics of conducting research. Each chapter ends with a summary of key takeaways from the chapter and exercises that do more than ask for content regurgitation. I find the organization of the textbook to be effective, and matches my approach to the course very well. I would not make any changes to the overall format with the exception of moving chapter 11 on presenting research to the end of the textbook, after the chapters on statistical analysis and interpretation.

I found the quality of the appearance of the textbook to be very good. The textbook features appropriate text and section/header font sizes that allow for an adequate zooming level to read large or smalls sections of text, that will give readers flexibility to match their personal preference. There are learning objectives at the start of each chapter to help students know what to expect. Key terms are highlighted in a separate color that are easily distinguishable in the body of the page. There are very useful visuals in every chapter, including tables, figures, and graphs. Relevant supplemental information is also highlighted in well formatted text boxes that are color coded to indicate what type of information is included. My only criticism is that the photographs included in the text are of low quality, and there are so few in the textbook that I feel it would have been better to just leave them out.

I found no grammatical errors in my review of the textbook. The textbook is generally well written, and the style of writing is at a level that is appropriate for an undergraduate class.

Although the textbook contains no instances of presenting information that is cultural insensitive or offensive, it does not offer an culturally inclusive review of information pertaining to research methods in psychology. I found no inclusion of examples of research conducting with non European American samples included in the summary of studies. Likewise the authors do place much attention on the issue of cultural sensitivity when conducing research. If there is one major weakness of the textbook I would say it is in this area, but based on my experience it is not an uncommon characteristic of textbooks on research methods in psychology.

Reviewed by zehra peynircioglu, Professor, American University on 2/1/18

Comprehensiveness rating: 3 see less

Short and sweet in most areas. Covers the basic concepts, not very comprehensively but definitely adequately so for a general beginning-level research methods course. For instance, I would liked to have seen a "separate" chapter on correlational research (there is one on single subject research and one on survey research), a discussion of the importance of providing a theoretical rationale for "getting an idea" (most students are fine with finding interesting and feasible project ideas but cannot give a theoretical rationale) before or after Chapter 4 on Theory, or a chapter on neuroscientific methods, which are becoming more and more popular. Nevertheless, it touches on most traditional areas that are in other books.

I did not find any errors or biases

This is one area where there is not much danger of going obsolete any time soon. The examples might need to be updated periodically (my students tend to not like dated materials, however relevant), but that should be easy.

Very clear and accessible prose. Despite the brevity, the concepts are put forth quite clearly. I like the "not much fluff" mentality. There is also adequate explanations of jargon and technical terminology.

I could not find any inconsistencies. The style and exposition frameworks are also quite consistent.

Yes, the modularity is fine. The chapters follow a logical pattern, so there should not be too much of a need for jumping around. And even if jumping around is needed depending on teaching style, the sections are solid in terms of being able to stand alone (or as an accompaniment to lectures).

Yes, the contents is ordered logically and the high modularity helps with any reorganization that an instructor may favor. In my case, for instance, Ch. 1 is fine, but I would skip it because it's mostly a repetition of what most introductory psychology books also say. I would also discuss non-experimental methods before going into experimental design. But such changes are easy to do, and if someone followed the book's own organization, there would also be a logical flow.

As far as I could see, the text is free of significant interface issues, at least in the pdf version

I could not find any errors.

As far as I could see, the book was culturally relevant.

I loved the short and sweet learning objectives, key takeaway sections, and the exercises. They are not overwhelming and can be used in class discussions, too.

Reviewed by George Woodbury, Graduate Student, Miami University, Ohio on 6/20/17

This text covers the typical areas for an undergraduate psychology course in research design. There is no table of contents included with the downloadable version, although there is a table of contents on the website (which excludes sub-sections of chapters). The sections on statistics are not extensive enough to be useful in and of themselves, but they are useful for transitions to a follow-up statistics course. There does not seem to be a glossary of terms, which made it difficult at times for my read through and I assume later for students who decide to print the text. The text is comprehensive without being wordy or tedious.

Relatively minor errors; There does not seem to be explicit cultural or methodological bias in the text.

The content is up-to-date, and examples from the psychology literature are generally within the last 25 years. Barring extensive restructuring in the fundamentals of methodology and design in psychology, any updates will be very easy to implement.

Text will be very clear and easy to read for students fluent in English. There is little jargon/technical terminology used, and the vocabulary that is provided in the text is contemporary

There do not seem to be obvious shifts in the terminology or the framework. The text is internally consistent in that regard.

The text is well divided into chapter and subsections. Each chapter is relatively self-contained, so there are little issues with referring to past material that may have been skipped. The learning objectives at the beginning of the chapter are very useful. Blocks of text are well divided with headings.

As mentioned above, the topics of the text follow the well-established trajectory of undergraduate psychology courses. This makes it very logical and clear.

The lack of a good table of contents made it difficult to navigate the text for my read through. There were links to an outside photo-hosting website (flickr) for some of the stock photos, which contained the photos of the original creators of the photos. This may be distracting or confusing to readers. However, the hyperlinks in general helped with navigation with the PDF.

No more grammatical errors than a standard, edited textbook.

Very few examples explicitly include other races, ethnicities, or backgrounds, however the examples seem to intentionally avoid cultural bias. Overall, the writing seems to be appropriately focused on avoiding culturally insensitive or offensive content.

After having examined several textbooks on research design and methodology related to psychology, this book stands out as superior.

Reviewed by Angela Curl, Assistant Professor, Miami University (Ohio) on 6/20/17

"Research Methods in Psychology" covers most research method topics comprehensively. The author does an excellent job explaining main concepts. The chapter on causation is very detailed and well-written as well as the chapter on research ethics. However, the explanations of data analysis seem to address upper level students rather than beginners. For example, in the “Describing Statistical Relationships” chapter, the author does not give detailed enough explanations for key terms. A reader who is not versed in research terminology, in my opinion, would struggle to understand the process. While most topics are covered, there are some large gaps. For example, this textbook has very little content related to qualitative research methods (five pages).

The content appears to be accurate and unbias.

The majority of the content will not become obsolete within a short time period-- many of the information can be used for the coming years, as the information provided is, overall, general in nature. The notably exceptions are the content on APA Code of Ethics and the APA Publication Manual, which both rely heavily on outdated versions, which limits the usefulness of these sections. In addition, it would be helpful to incorporate research studies that have been published after 2011.

The majority of the text is clear, with content that is easy for undergraduate students to read and understand. The key points included in the chapters are helpful, but some chapters seem to be missing key points (i.e., the key points do not accurately represent the overall chapter).

The text seems to be internally consistent in its terminology and organization.

Each chapter is broken into subsections that can be used alone. For example, section 5.2 covers reliability and validity of measurement. This could be extremely helpful for educators to select specific content for assigned readings.

The topics are presented in a logical matter for the most part. However, the PDF version of the book does not include a table of contents, and none of the formats has a glossary or index. This can make it difficult to quickly navigate to specific topics or terms, especially when explanations do not appear where expected. For example, the definitions of independent and dependent variables is provided under the heading “Correlation Does Not Imply Causation” (p. 22).

The text is consistent but needs more visual representations throughout the book, rather than heavily in some chapters and none at all in other chapters. Similarly, the text within the chapters is not easily readable due to the large sections of text with little to no graphics or breaks.

The interface of the text is adequate. However, the formatting of the PDF is sometimes weak. For example, the textbook has a number of pages with large blank spaces and other pages are taken up with large photos or graphics. The number of pages (and cost of printing) could have been reduced, or more graphics added to maximize utility.

I found no grammatical errors.

Text appears to be culturally sensitive. I appreciated the inclusion of the content about avoiding biased language (chapter 11).

Instructors who adopt this book would likely benefit from either selecting certain chapters/modules and/or integrating multiple texts together to address the shortcomings of this text. Further, the sole focus on psychology limits the use of this textbook for introductory research methods for other disciplines (e.g., social work, sociology).

Reviewed by Pramit Nadpara, Assistant Professor, Virginia Commonwealth University on 4/11/17

The text book provides good information in certain areas, while not comprehensive information in other areas. The text provides practical information, especially the section on survey development was good. Additional information on sampling... read more

There are no errors.

Research method is a common topic and the fundamentals of it will not change over the years. Therefore, the book is relevant and will not become obsolete.

Clarity rating: 3

The text in the book is clear. Certain aspects of the text could have been presented more clearly. For example, the section on main effects and interactions are some concepts that students may have difficulty understanding. Those areas could be explained more clearly with an example.

Consistency rating: 3

Graphs in the book lacks titles and variable names. Also, the format of chapter title page needs to be consistent.

At times there were related topics spread across several chapters. This could be corrected for a better read by the audience..

The book text is very clear, and the flow from one topic to the next was adequate. However, having a outline would help the reader.

The PDF copy of the book was a easy read. There were few links that were missing though.

There were no grammatical errors.

The text is not offensive and examples in it are mostly based on historical US based experiments.

I would start of by saying that I am a supporter of the Open Textbook concept. In this day and age, there are a variety of Research Methods book/text available on the market. While this book covers research methods basics, it cannot be recommended in its current form as an acceptable alternative to the standard text. Modifications to the text as recommended by myself and other reviewers might improve the quality of this book in the future.

Reviewed by Meghan Babcock, Instructor, University of Texas at Arlington on 4/11/17

This text includes all important areas that are featured in other Research Methods textbooks and are presented in a logical order. The text includes great examples and provides the references which can be assigned as supplemental readings. In addition, the chapters end with exercises that can be completed in class or as part of a laboratory assignment. This text would be a great addition to a Research Methods course or an Introductory Statistics course for Psychology majors.

The content is accurate. I did not find any errors and the material is unbiased.

Yes - the content is up to date and would be easy to update if/when necessary.

The text is written at an appropriate level for undergraduate students and explains important terminology. The research studies that the author references are ones that undergraduate psychology majors should be familiar with. The only section that was questionable to me was that on multiple regression in section 8.3 (Complex Correlational Designs). I am unaware of other introductory Research Methods textbooks that cover this analysis, especially without describing simple regression first.

The text is consistent in terms of terminology. The framework is also consistent - the chapters begin with Learning Objectives and ends with Key Takeaways and Exercises.

The text is divisible into smaller reading sections - possibly too many. The sections are brief, and in some instances too brief (e.g., the section on qualitative research). I think that the section headers are helpful for instructors who plan on using this text in conjunction with another text in their course.

The topics were presented in a logical fashion and are similar to other published Research Methods texts. The writing is very clear and great examples are provided. I think that some of the sections are rather brief and more information and examples could be provided.

I did not see any interface issues. All of the links worked properly and the tables and figures were accurate and free of errors. I particularly liked the figures in section 5.2 on reliability of measurement.

There are three comments that I have about the interface, however. First, I was expecting the keywords in blue font to be linked to a glossary, but they were not. I would have appreciated this feature. Second, I read this text as a PDF on an iPad and this version lacking was the Table of Contents (TOC) feature. Although I was able to view the TOC in different versions, I would have appreciated it in the PDF version. Also, it would be nice if the TOC was clickable (i.e., you could click on a section and it automatically directed you to that section). Third, I think the reader of this text would benefit from a glossary at the end of each chapter and/or an index at the end of the text. The "Key Takeaways" sections at the end of each chapter were helpful, but I think that a glossary would be a nice addition as well.

I did not notice any grammatical errors of any kind. The text was easy to read and I think that undergraduate students would agree.

The text was not insensitive or offensive to any races, ethnicities, or backgrounds. I appreciated the section on avoiding biased language when writing manuscripts (e.g., using 'children with learning disabilities' instead of 'special children' or using 'African American' instead of 'minority').

I think that this text would be a nice addition to a Research Methods & Statistics course in psychology. There are some sections that I found particularly helpful: (1) 2.2 and 2.3 - the author gives detailed information about generating research questions and reviewing the literature; (2) 9.2 - this section focuses on constructing survey questionnaires; (3) 11.2 and 11.3 - the author talks about writing a research report and about presenting at conferences. These sections will be great additions to an undergraduate Research Methods course. The brief introduction to APA style was also helpful, but should be supplemented with the most recent APA style manual.

Reviewed by Shannon Layman, Lecturer, University of Texas at Arlington on 4/11/17

The sections in this textbook are overall more brief than in previous Methods texts that I have used. Sometimes this brevity is helpful in terms of getting to the point of the text and moving on. In other cases, some topics could use a bit more... read more

I did not find any incorrect information or gross language issues.

Basic statistical and/or methodological texts tend to stay current and up-to-date because the topics in this field have not changed over the decades. Any updated methodologies would be found in a more advanced methods text.

The text is very clear and the ideas are easy to follow/ presented in a logical manner. The most helpful thing about this textbook is that the author arrives at the point of the topic very quickly. Another helpful point about this textbook is the relevancy of the examples used. The examples appear to be accessible to a wide audience and do not require specialization or previous knowledge of other fields of psychology.

I feel this text is very consistent throughout. The ideas build on each other and no terms are discussed in later chapters without being established in previous chapters.

Each chapter had multiple subsections which would allow for smaller reading sections throughout the course. The amount of content in each section and chapter appeared to be less than what I have encountered in other Methods texts.

The organization of the topics in this textbook follows the same or similar organization that I see in other textbooks. As I mentioned previously, the ideas build very well throughout the text.

I did not find any issues with navigation or distortion of the figures in the text.

There were not any obvious and/or egregious grammatical errors that I encountered in this text.

This topic is not really an issue with a Methods textbook as the topics are more so conceptual as opposed to topical. That being said, I did not see an issue with any examples used.

I have no other comments than what I addressed previously.

Reviewed by Sarah Allred, Associate Professor, Rutgers University, Camden on 2/8/17

Mixed. For some topics, there is more (and more practical) information than in most textbooks. I appreciated the very practical advice to students about how to plot data (in statistics chapters). Similarly, there is practical advice about how... read more

On the other hand, there is far too little information about some subjects. For example, independent and dependent variables are introduced in passing in an early chapter and then referred to only much later in the text. In my experience, students have a surprisingly difficult time grasping this concept. Another important example is sampling; I would have preferred much more information on types of samples and sampling techniques, and the problems that arise from poor sampling. A third example is the introduction to basic experimental design. Variables, measurement, validity, and reliability are all introduced in one chapter.

I did not see an index or glossary.

I found no errors.

The fundamentals of research methods do not change much. Given the current replication crisis in psychology, it might be helpful to have something about replicability.

Mixed. The text itself is spare and clear. The style of the book is to explain a concept in very few words. There are some excellent aspects of this, but on the other hand, there are some concepts that students have a very difficult time undersatnding if they are not embedded in concrete examples. For example, the section on main effects and interactions shows bar graphs of interactions, but this is presented without variable names or axis titles, and separate from any specific experiment.

Sometimes the chapter stucture is laid out on the title page, and other times it is not. Some graphs lack titles and variable names.

The chapters can be stand alone, but sometimes I found conceptually similar pieces spread across several chapters, and conceptually different pieces in the same chapters.

The individual sentences and paragraphs are always very clear. However, I felt that more tables/outlines of major concepts would have been helpful. For example, perhaps a flow chart of different kinds of experimental designs would be useful. (See section on comprehensiveness for more about organization).

The flow from one topic to the next was adequate.

I read the pdf. Perhaps the interface is more pleasant on other devices, but I found the different formats and fonts in image/captions/main text/figure labels distracting. Many if the instances of apparently hyperlinked (blue) text to do not link to anything.

I found no grammatical errors, and prose is standard academic English.

Like most psychology textbooks available in the US, examples are focused on important experiments in US history.

I really wanted to be happy with this text. I am a supporter of the Open Textbook concept, and I wanted to find this book an acceptable alternative to the variety of Research Methods texts I’ve used. Unfortunately, I cannot recommend this book as superior in quality.

Reviewed by Joel Malin, Assistant Professor, Miami University on 8/21/16

This textbook covers all or nearly all of what I believe are important topics to provide an introduction to research methods in psychology. One minor issue is that the pdf version, which I reviewed, does not include an index or a glossary. As such, it may be difficult for readers to zero in on material that they need, and/or to get a full sense of what will be covered and in what order.

I did not notice errors.

The book provides a solid overview of key issues related to introductory research methods, many of which are nearly timeless.

The writing is clear and accessible. It was easy and pleasing to read.

Terms are clearly defined and build upon each other as the book progresses.

I believe the text is organized in such a way that it could be easily divided into smaller sections.

The order in which material is presented seems to be well thought out and sensible.

I did not notice any issues with the interface. I reviewed the pdf version and thought the images were very helpful.

The book is written in a culturally relevant manner.

Reviewed by Abbey Dvorak, Assistant Professor, University of Kansas on 8/21/16

The text includes basic, essential information needed for students in an introductory research methods course. In addition, the text includes three chapters (i.e., research ethics, theory, and APA style) that are typically absent from or inadequately covered in similar texts. However, I did have some areas of concern regarding the coverage of qualitative and mixed methods approaches, and nonparametric tests. Although the author advocates for the research question to guide the choice of approach and design, minimal attention is given to the various qualitative designs (e.g., phenomenology, narrative, participatory action, etc.) beyond grounded theory and case studies, with no mention of the different types of mixed methods designs (e.g., concurrent, explanatory, exploratory) that are prevalent today. In addition, common nonparametric tests (e.g., Wilcoxon, Mann-Whitney, etc.) and parametric tests for categorical data (e.g., chi-square, Fisher’s exact, etc.) are not mentioned.

The text overall is accurate and free of errors. I noticed in the qualitative research sub-section, the author describes qualitative research in general, but does not mention common practices associated with qualitative research, such as transcribing interviews, coding data (e.g., different approaches to coding, different types of codes), and data analysis procedures. The information that is included appears accurate.

The text appears up-to-date and includes basic research information and classic examples that rarely change, which may allow the text to be used for many years. However, the author may want to add information about mixed methods research, a growing research approach, in order for the text to stay relevant across time.

The text includes clear, accessible, straightforward language with minimal jargon. When the author introduces a new term, the term is immediately defined and described. The author also provides interesting examples to clarify and expand understanding of terms and concepts throughout the text.

The text is internally consistent and uses similar language and vocabulary throughout. The author uses real-life examples across chapters in order to provide depth and insight into the information. In addition, the vocabulary, concepts, and organization are consistent with other research methods textbooks.

The modules are short, concise, and manageable for students; the material within each module is logically focused and related to each other. I may move the modules and the sub-topics within them into a slightly different order for my class, and add the information mentioned above, but overall, this is very good.

The author presents topics and structures chapters in a logical and organized manner. The epub and online version do not include page numbers in the text, but the pdf does; this may be confusing when referencing the text or answering student questions. The book ends somewhat abruptly after the chapter on inferential statistics; the text may benefit from a concluding chapter to bring everything together, perhaps with a culminating example that walks the reader through creating the research question, choosing a research approach/design, etc., all the way to writing the research report.

I used and compared the pdf, epub, and online versions of the text. The epub and online versions include a clickable table of contents, but the pdf does not. The table format is inconsistent across the three versions; in the epub version (viewed through ibooks), the table data does not always line up correctly, making it difficult to interpret quickly. In the pdf and online versions, the table format looks different, but the data are lined up. No index made it difficult to quickly find areas of interest in the text; however, I could use the Find/Search functions in all three versions to search and find needed items.

As I read through this text, I did not detect any glaring grammatical errors. Overall, I think the text is written quite well in a style that is accessible to students.

The author uses inclusive, person-first language, and the text does not seem to be offensive or insensitive. As I read, I did notice that topics such as diversity and cultural competency are absent.

I enjoyed reading this text and am very excited to have a free research methods text for my students that I may supplement as needed. I wish there was a test question bank and/or flashcards for my students to help them study, but perhaps that could be added in the future. Overall, this is a great resource!

Reviewed by Karen Pikula, Psychology Instructor PhD, Central Lakes College on 1/7/16

The text covers all the areas and ideas of the subject of research methods in psychology for the learner that is just entering the field. The authors cover all of the content of an introductory research methods textbook and use exemplary examples that make those concepts relevent to a beginning researcher. As the authors state, the material is presented in such a manner as to encourage learners to not only be effective consumers of current research but also engage as critical thinkers in the many diverse situations one encounters in everyday life.

The content is accurate, error free, and unbiased. It explains both quantiative and qualitative methods in an unbiased manner. It is a bit slim on qualitative. It would be nice to have a bit more information on, for example, creating interview questions, coding, and qualitative data anaylisis.

The text is up to date, having just been revised. This revision was authored by Rajiv Jhangiani (Capilano University, North Vancouver) and includes the addition of a table of contents and cover page that the original text did not have, changes to Chapter 3 (Research Ethics) to include a contemporary example of an ethical breach and to reflect Canadian ethical guidelines and privacy laws, additional information regarding online data collection in Chapter 9 (Survey Research). Jhangiani has correcte of errors in the text and formulae, as well as changing spelling from US to Canadian conventions. The text is also now available in a inexpensive hard copy which students can purchase online or college bookstores can stock. This makes the text current and updates should be minimal.

The text is very easy to read and also very interesting as the authors supplement content with amazing real life examples.

The text is internally consistent in terms of terminology and framework.

This text is easily and readily divisible into smaller reading sections that can be assigned at different points within a course. I am going to use this text in conjunction with the OER OpenStax Psychology text for my Honors Psychology course. I currently use the OER Openstax Psychology textbook for my Positive Psychology course as well as my General Psychology course,

The topics in the text are presented in logical and clear fashion. The way they are presented allows the text to be used in conjuction with other textbooks as a secondary resource.

The text is free of significant interface issues. It is written in a manner that follows the natural process of doing research.

The text contained no noted grammatical errors.

The text is not culturally insensitive or offensive and actually has been revised to accomodate Canadian ethical guidelines as well as those of the APA.

I have to say that I am excited to have found this revised edition. My students will be so happy that there is also a reasonable priced hard coopy for them to purchase. They love the OpenStax Psychology text with the hard copy available from our bookstore. I do wish there were PowerPoints available for the text as well as a test bank. That is always a bonus!

Reviewed by Alyssa Gibbons, Instructor, Colorado State University on 1/7/16

This text covers everything I would consider essential for a first course in research methods, including some areas that are not consistently found in introductory texts (e.g., qualitative research, criticisms of null hypothesis significance testing). The chapters on ethics (Ch. 3) and theory (Ch. 4) are more comprehensive than most I have seen at this level, but not to the extent of information overload; rather, they anticipate and address many questions that undergraduates often have about these issues.

There is no index or table of contents provided in the PDF, and the table of contents on the website is very broad, but the material is well organized and it would not be hard for an instructor to create such a table. Chapter 2.1 is intended to be an introduction to several key terms and ideas (e.g., variable, correlation) that could serve as a sort of glossary.

I found the text to be highly accurate throughout; terms are defined precisely and correctly.

Where there are controversies or differences of opinion in the field, the author presents both sides of the argument in a respectful and unbiased manner. He explicitly discourages students from dismissing any one approach as inherently flawed, discussing not only the advantages and disadvantages of all methods (including nonexperimental ones) but also ways researchers address the disadvantages.

In several places, the textbook explicitly addresses the history and development of various methods (e.g., qualitative research, null hypothesis significance testing) and the ways in which researchers' views have changed. This allows the author to present current thinking and debate in these areas yet still expose students to older ideas they are likely to encounter as they read the research literature. I think this approach sets students up well to encounter future methodological advances; as a field, we refine our methods over time. I think the author could easily integrate new developments in future editions, or instructors could introduce such developments as supplementary material without creating confusion by contradicting the test.

The examples are generally drawn from classic psychological studies that have held up well over time; I think they will appeal to students for some time to come and not appear dated.

The only area in which I did not feel the content was entirely up to date was in the area of psychological measurement; Chapter 5.2 is based on the traditional view and not the more comprehensive modern or holistic view as presented in the 1999 AERA/APA Standards for Educational and Psychological Measurement. However, a comprehensive treatment of measurement validity is probably not necessary for most undergraduates at this stage, and they will certainly encounter the older framework in the research literature.

The textbook does an excellent job of presenting concepts in simple, accessible language without introducing error by oversimplification. The author consistently anticipates common points of confusion, clarifies terms, and even suggests ways for students to remember key distinctions. Terms are clearly and concretely defined when they are introduced. In contrast to many texts I have used, the terms that are highlighted in the text are actually the terms I would want my students to remember and study; the author refrains from using psychological jargon that is not central to the concepts he is discussing.

I noticed no major inconsistencies or gaps.

The division of sections within each chapter is useful; although I liked the overall organization of the text, there were points at which I would likely assign sections in a slightly different order and I felt I could do this easily without loss of continuity. The one place I would have liked more modularity was in the discussion of inferential statistics: t-tests, ANOVA, and Pearson's r are all covered within Chapter 13.2. On the one hand, this enables students to see the relationships and similarities among these tests, but on the other, this is a lot for students to take in at once.

I found the overall organization of the book to be quite logical, mirroring the sequence of steps a researcher would use to develop a research question, design a study, etc. As discussed above, the modularity of the book makes it easy to reorder sections to suit the structure of a particular class (for example, I might have students read the section on APA writing earlier in the semester as they begin drafting their own research proposals). I like the inclusion of ethics very early on in the text, establishing the importance of this topic for all research design choices.

One organizational feature I particularly appreciated was the consistent integration of conceptual and practical ideas; for example, in the discussion of psychological measurement, reliability and validity are discussed alongside the importance of giving clear instructions and making sure participants cannot be identified by their writing implements. This gives students an accurate and honest picture of the research process - some of the choices we make are driven by scientific ideals and some are driven by practical lessons learned. Students often have questions related to these mundane aspects of conducting research and it is helpful to have them so clearly addressed.

Although I didn't encounter any problems per se with the interface, I do think it could be made more user-friendly. For example, references to figures and tables are highlighted in blue, appearing to be hyperlinks, but they were not. Having such links, as well as a linked, easily-navigable and detailed table of contents, would also be helpful (and useful to students who use assistive technology).

I noticed no grammatical errors.

Where necessary, the author uses inclusive language and there is nothing that seems clearly offensive. The examples generally reflect American psychology research, but the focus is on the methods used and not the participants or cultural context. The text could be more intentionally or proactively inclusive, but it is not insensitive or exclusive.

I am generally hard to please when it comes to textbooks, but I found very little to quibble with in this one. It is a very well-written and accessible introduction to research methods that meets students where they are, addressing their common questions, misconceptions, and concerns. Although it's not flashy, the figures, graphics, and extra resources provided are clear, helpful, and relevant.

Reviewed by Moin Syed, Assistant Professor, University of Minnesota on 6/10/15

The text is thorough in terms of covering introductory concepts that are central to experimental and correlational/association designs. I find the general exclusion of qualitative and mixed methods designs hard to defend (despite some researchers’ distaste for the methods). While these approaches were less commonly used in the recent past, they are prevalent in the early years of psychology and are ascending once again. It strikes me as odd to just ignore two whole families of methods that are used within the practice of psychology—definitely not a sustainable approach.

I do very much appreciate the emphasis on those who will both practice and consume psychology, given the wide variety of undergraduate career paths.

One glaring omission is a Table of Contents within the PDF. It would be nice to make this a linked PDF, so that clicking on the entry in a TOC (or cross-references) would jump the reader to the relevant section.

I did not see an errors. The chapter on theory is not as clear as it could be. The section “what is theory” is not very clear, and these are difficulte concepts (difference between theory, hypothesis, etc.). A bit more time spent here could have been good. Also, the discussion of functional, mechanistic, and typological theories leaves out the fourth of Pepper’s metaphors: contextualism. I’m not sure that was intentional and accidental, but it is noticeable!

This is a research methods text focused on experimental and association designs. The basics of these designs do not change a whole lot over time, so there is little likelihood that the main content will become obsolete anytime soon. Some of the examples used are a bit dated, but then again most of them are considered “classics” in the field, which I think are important to retain (and there is at least one “new classic” included in the ethics section, namely the fraudulent research linking autism to the MMR vaccine).

The text is extremely clear and accessible. In fact, it may even be *too* simple for undergraduate use. Then again, students often struggle with methods, so simplicity is good, and the simplicity can also make the book marketable to high school courses (although I doubt many high schools have methods courses).

Yes, quite consistent throughout. Carrying through the same examples into different chapters is a major strength of the text.

I don’ anticipate any problems here.

The book flows well, with brief sections. I do wonder if maybe the sections are too brief? Perhaps too many check-ins? The “key take-aways” usually come after only a few pages. As mentioned above, the book is written at a very basic level, so this brevity is consistent with that approach. It is not a problem, per se, but those considering adopting the text should be aware of this aspect.

No problems here.

I did not detect any grammatical errors. The text flows very well.

The book is fairly typical of American research methods books in that it only focuses on the U.S. context and draws its examples from “mainstream” psychology (e.g., little inclusion of ethnic minority or cross-cultural psychology). However, the text is certainly not insensitive or offensive in any way.

Nice book, thanks for writing it!

Reviewed by Rajiv Jhangiani, Instructor, Capilano University on 10/9/13

The text is well organized and written, integrates excellent pedagogical features, and covers all of the traditional areas of the topic admirably. The final two chapters provide a good bridge between the research methods course and the follow-up course on behavioural statistics. The text integrates real psychological measures, harnesses students' existing knowledge from introductory psychology, includes well-chosen examples from real life and research, and even includes a very practical chapter on the use of APA style for writing and referencing. On the other hand, it does not include a table of contents or an index, both of which are highly desirable. The one chapter that requires significant revision is Chapter 3 (Research Ethics), which is based on the US codes of ethics (e.g., Federal policy & APA code) and does not include any mention of the Canadian Tri-Council Policy Statement.

The very few errors I found include the following: 1. The text should read "The fact that his F score…" instead of "The fact that his t score…" on page 364 2. Some formulae are missing the line that separates the numerator from the denominator. See pages 306, 311, 315, and 361 3. Table 12.3 on page 310 lists the variance as 288 when it is 28.8

The text is up-to-date and will not soon lose relevance. The only things I would add are a brief discussion of the contemporary case of Diederik Stapel's research fraud in the chapter on Research Ethics, as well as some research concerning the external validity of web-based studies (e.g., Gosling et al.'s 2004 article in American Psychologist).

Overall, the style of writing makes this text highly accessible. The writing flows well, is well organized, and includes excellent, detailed, and clear examples and explanations for concepts. The examples often build on concepts or theories students would have covered in their introductory psychology course. Some constructive criticism: 1. When discussing z scores on page 311 it might have been helpful to point out that the mean and SD for a set of calculated z scores are 0 and 1 respectively. Good students will come to this realization themselves, but it is not a bad thing to point it out nonetheless. 2. The introduction of the concept of multiple regression might be difficult for some students to grasp. 3. The only place where I felt short of an explanation was in the use of a research example to demonstrate the use of a line graph on page 318. In this case the explanation in question does not pertain to the line graph itself but the result of the study used, which is so fascinating that students will wish for the researchers' explanation for it.

The text is internally consistent.

The text is organized very well into chapters, modules within each chapter, and learning objectives within each module. Each module also includes useful exercises that help consolidate learning.

As mentioned earlier, the style of writing makes this text highly accessible. The writing flows well, is well organized, and includes excellent, detailed, and clear examples and explanations for concepts. The examples often build on concepts or theories students would have covered in their introductory psychology course. Only rarely did I feel that the author could have assisted the student by demonstrating the set-by-step calculation of a statistic (e.g., on page 322 for the calculation of Pearson's r)

The images, graphs, and charts are clear. The only serious issues that hamper navigation are the lack of a table of contents and an index. Many of the graphs will need to be printed in colour (or otherwise modified) for the students to follow the explanations provided in the text.

The text is written rather well and is free from grammatical errors. Of course, spellings are in the US convention.

The text is not culturally insensitive or offensive. Of course, it is not a Canadian edition and so many of the examples (all of which are easy to comprehend) come from a US context.

I have covered most of these issues in my earlier comments. The only things left to mention are that the author should have clearly distinguished between mundane and psychological realism, and that, in my opinion, the threats to internal validity could have been grouped together and might have been closer to an exhaustive list. This review originated in the BC Open Textbook Collection and is licensed under CC BY-ND.

Chapter 1: The Science of Psychology
Chapter 2: Overview of the Scientific Method
Chapter 3: Research Ethics
Chapter 4: Psychological Measurement
Chapter 5: Experimental Research
Chapter 6: Non-experimental Research
Chapter 7: Survey Research
Chapter 8: Quasi-Experimental Research
Chapter 9: Factorial Designs
Chapter 10: Single-Subject Research
Chapter 11: Presenting Your Research
Chapter 12: Descriptive Statistics
Chapter 13: Inferential Statistics

Ancillary Material

Kwantlen Polytechnic University

About the Book

This fourth edition (published in 2019) was co-authored by Rajiv S. Jhangiani (Kwantlen Polytechnic University), Carrie Cuttler (Washington State University), and Dana C. Leighton (Texas A&M University—Texarkana) and is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Revisions throughout the current edition include changing the chapter and section numbering system to better accommodate adaptions that remove or reorder chapters; continued reversion from the Canadian edition; general grammatical edits; replacement of “he/she” to “they” and “his/her” to “their”; removal or update of dead links; embedded videos that were not embedded; moved key takeaways and exercises from the end of each chapter section to the end of each chapter; a new cover design.

About the Contributors

Dr. Carrie Cuttler received her Ph.D. in Psychology from the University of British Columbia. She has been teaching research methods and statistics for over a decade. She is currently an Assistant Professor in the Department of Psychology at Washington State University, where she primarily studies the acute and chronic effects of cannabis on cognition, mental health, and physical health. Dr. Cuttler was also an OER Research Fellow with the Center for Open Education and she conducts research on open educational resources. She has over 50 publications including the following two published books: A Student Guide for SPSS (1st and 2nd edition) and Research Methods in Psychology: Student Lab Guide. Finally, she edited another OER entitled Essentials of Abnormal Psychology. In her spare time, she likes to travel, hike, bike, run, and watch movies with her husband and son. You can find her online at @carriecuttler or carriecuttler.com.

Dr. Rajiv Jhangiani is the Associate Vice Provost, Open Education at Kwantlen Polytechnic University in British Columbia. He is an internationally known advocate for open education whose research and practice focuses on open educational resources, student-centered pedagogies, and the scholarship of teaching and learning. Rajiv is a co-founder of the Open Pedagogy Notebook, an Ambassador for the Center for Open Science, and serves on the BC Open Education Advisory Committee. He formerly served as an Open Education Advisor and Senior Open Education Research & Advocacy Fellow with BCcampus, an OER Research Fellow with the Open Education Group, a Faculty Workshop Facilitator with the Open Textbook Network, and a Faculty Fellow with the BC Open Textbook Project. A co-author of three open textbooks in Psychology, his most recent book is Open: The Philosophy and Practices that are Revolutionizing Education and Science (2017). You can find him online at @thatpsychprof or thatpsychprof.com.

Dr. Dana C. Leighton is Assistant Professor of Psychology in the College of Arts, Science, and Education at Texas A&M University—Texarkana. He earned his Ph.D. from the University of Arkansas, and has 15 years experience teaching across the psychology curriculum at community colleges, liberal arts colleges, and research universities. Dr. Leighton’s social psychology research lab studies intergroup relations, and routinely includes undergraduate students as researchers. He is also Chair of the university’s Institutional Review Board. Recently he has been researching and writing about the use of open science research practices by undergraduate researchers to increase diversity, justice, and sustainability in psychological science. He has published on his teaching methods in eBooks from the Society for the Teaching of Psychology, presented his methods at regional and national conferences, and received grants to develop new teaching methods. His teaching interests are in undergraduate research, writing skills, and online student engagement. For more about Dr. Leighton see http://www.danaleighton.net and http://danaleighton.edublogs.org

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Chapter 5. Sampling

Introduction.

Most Americans will experience unemployment at some point in their lives. Sarah Damaske ( 2021 ) was interested in learning about how men and women experience unemployment differently. To answer this question, she interviewed unemployed people. After conducting a “pilot study” with twenty interviewees, she realized she was also interested in finding out how working-class and middle-class persons experienced unemployment differently. She found one hundred persons through local unemployment offices. She purposefully selected a roughly equal number of men and women and working-class and middle-class persons for the study. This would allow her to make the kinds of comparisons she was interested in. She further refined her selection of persons to interview:

I decided that I needed to be able to focus my attention on gender and class; therefore, I interviewed only people born between 1962 and 1987 (ages 28–52, the prime working and child-rearing years), those who worked full-time before their job loss, those who experienced an involuntary job loss during the past year, and those who did not lose a job for cause (e.g., were not fired because of their behavior at work). ( 244 )

The people she ultimately interviewed compose her sample. They represent (“sample”) the larger population of the involuntarily unemployed. This “theoretically informed stratified sampling design” allowed Damaske “to achieve relatively equal distribution of participation across gender and class,” but it came with some limitations. For one, the unemployment centers were located in primarily White areas of the country, so there were very few persons of color interviewed. Qualitative researchers must make these kinds of decisions all the time—who to include and who not to include. There is never an absolutely correct decision, as the choice is linked to the particular research question posed by the particular researcher, although some sampling choices are more compelling than others. In this case, Damaske made the choice to foreground both gender and class rather than compare all middle-class men and women or women of color from different class positions or just talk to White men. She leaves the door open for other researchers to sample differently. Because science is a collective enterprise, it is most likely someone will be inspired to conduct a similar study as Damaske’s but with an entirely different sample.

This chapter is all about sampling. After you have developed a research question and have a general idea of how you will collect data (observations or interviews), how do you go about actually finding people and sites to study? Although there is no “correct number” of people to interview, the sample should follow the research question and research design. You might remember studying sampling in a quantitative research course. Sampling is important here too, but it works a bit differently. Unlike quantitative research, qualitative research involves nonprobability sampling. This chapter explains why this is so and what qualities instead make a good sample for qualitative research.

Quick Terms Refresher

The population is the entire group that you want to draw conclusions about.
The sample is the specific group of individuals that you will collect data from.
Sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).
Sample size is how many individuals (or units) are included in your sample.

The “Who” of Your Research Study

After you have turned your general research interest into an actual research question and identified an approach you want to take to answer that question, you will need to specify the people you will be interviewing or observing. In most qualitative research, the objects of your study will indeed be people. In some cases, however, your objects might be content left by people (e.g., diaries, yearbooks, photographs) or documents (official or unofficial) or even institutions (e.g., schools, medical centers) and locations (e.g., nation-states, cities). Chances are, whatever “people, places, or things” are the objects of your study, you will not really be able to talk to, observe, or follow every single individual/object of the entire population of interest. You will need to create a sample of the population . Sampling in qualitative research has different purposes and goals than sampling in quantitative research. Sampling in both allows you to say something of interest about a population without having to include the entire population in your sample.

We begin this chapter with the case of a population of interest composed of actual people. After we have a better understanding of populations and samples that involve real people, we’ll discuss sampling in other types of qualitative research, such as archival research, content analysis, and case studies. We’ll then move to a larger discussion about the difference between sampling in qualitative research generally versus quantitative research, then we’ll move on to the idea of “theoretical” generalizability, and finally, we’ll conclude with some practical tips on the correct “number” to include in one’s sample.

Sampling People

To help think through samples, let’s imagine we want to know more about “vaccine hesitancy.” We’ve all lived through 2020 and 2021, and we know that a sizable number of people in the United States (and elsewhere) were slow to accept vaccines, even when these were freely available. By some accounts, about one-third of Americans initially refused vaccination. Why is this so? Well, as I write this in the summer of 2021, we know that some people actively refused the vaccination, thinking it was harmful or part of a government plot. Others were simply lazy or dismissed the necessity. And still others were worried about harmful side effects. The general population of interest here (all adult Americans who were not vaccinated by August 2021) may be as many as eighty million people. We clearly cannot talk to all of them. So we will have to narrow the number to something manageable. How can we do this?

First, we have to think about our actual research question and the form of research we are conducting. I am going to begin with a quantitative research question. Quantitative research questions tend to be simpler to visualize, at least when we are first starting out doing social science research. So let us say we want to know what percentage of each kind of resistance is out there and how race or class or gender affects vaccine hesitancy. Again, we don’t have the ability to talk to everyone. But harnessing what we know about normal probability distributions (see quantitative methods for more on this), we can find this out through a sample that represents the general population. We can’t really address these particular questions if we only talk to White women who go to college with us. And if you are really trying to generalize the specific findings of your sample to the larger population, you will have to employ probability sampling , a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population randomly. Why randomly? If truly random, all the members have an equal opportunity to be a part of the sample, and thus we avoid the problem of having only our friends and neighbors (who may be very different from other people in the population) in the study. Mathematically, there is going to be a certain number that will be large enough to allow us to generalize our particular findings from our sample population to the population at large. It might surprise you how small that number can be. Election polls of no more than one thousand people are routinely used to predict actual election outcomes of millions of people. Below that number, however, you will not be able to make generalizations. Talking to five people at random is simply not enough people to predict a presidential election.

In order to answer quantitative research questions of causality, one must employ probability sampling. Quantitative researchers try to generalize their findings to a larger population. Samples are designed with that in mind. Qualitative researchers ask very different questions, though. Qualitative research questions are not about “how many” of a certain group do X (in this case, what percentage of the unvaccinated hesitate for concern about safety rather than reject vaccination on political grounds). Qualitative research employs nonprobability sampling . By definition, not everyone has an equal opportunity to be included in the sample. The researcher might select White women they go to college with to provide insight into racial and gender dynamics at play. Whatever is found by doing so will not be generalizable to everyone who has not been vaccinated, or even all White women who have not been vaccinated, or even all White women who have not been vaccinated who are in this particular college. That is not the point of qualitative research at all. This is a really important distinction, so I will repeat in bold: Qualitative researchers are not trying to statistically generalize specific findings to a larger population . They have not failed when their sample cannot be generalized, as that is not the point at all.

In the previous paragraph, I said it would be perfectly acceptable for a qualitative researcher to interview five White women with whom she goes to college about their vaccine hesitancy “to provide insight into racial and gender dynamics at play.” The key word here is “insight.” Rather than use a sample as a stand-in for the general population, as quantitative researchers do, the qualitative researcher uses the sample to gain insight into a process or phenomenon. The qualitative researcher is not going to be content with simply asking each of the women to state her reason for not being vaccinated and then draw conclusions that, because one in five of these women were concerned about their health, one in five of all people were also concerned about their health. That would be, frankly, a very poor study indeed. Rather, the qualitative researcher might sit down with each of the women and conduct a lengthy interview about what the vaccine means to her, why she is hesitant, how she manages her hesitancy (how she explains it to her friends), what she thinks about others who are unvaccinated, what she thinks of those who have been vaccinated, and what she knows or thinks she knows about COVID-19. The researcher might include specific interview questions about the college context, about their status as White women, about the political beliefs they hold about racism in the US, and about how their own political affiliations may or may not provide narrative scripts about “protective whiteness.” There are many interesting things to ask and learn about and many things to discover. Where a quantitative researcher begins with clear parameters to set their population and guide their sample selection process, the qualitative researcher is discovering new parameters, making it impossible to engage in probability sampling.

Looking at it this way, sampling for qualitative researchers needs to be more strategic. More theoretically informed. What persons can be interviewed or observed that would provide maximum insight into what is still unknown? In other words, qualitative researchers think through what cases they could learn the most from, and those are the cases selected to study: “What would be ‘bias’ in statistical sampling, and therefore a weakness, becomes intended focus in qualitative sampling, and therefore a strength. The logic and power of purposeful sampling like in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposeful sampling” ( Patton 2002:230 ; emphases in the original).

Before selecting your sample, though, it is important to clearly identify the general population of interest. You need to know this before you can determine the sample. In our example case, it is “adult Americans who have not yet been vaccinated.” Depending on the specific qualitative research question, however, it might be “adult Americans who have been vaccinated for political reasons” or even “college students who have not been vaccinated.” What insights are you seeking? Do you want to know how politics is affecting vaccination? Or do you want to understand how people manage being an outlier in a particular setting (unvaccinated where vaccinations are heavily encouraged if not required)? More clearly stated, your population should align with your research question . Think back to the opening story about Damaske’s work studying the unemployed. She drew her sample narrowly to address the particular questions she was interested in pursuing. Knowing your questions or, at a minimum, why you are interested in the topic will allow you to draw the best sample possible to achieve insight.

Once you have your population in mind, how do you go about getting people to agree to be in your sample? In qualitative research, it is permissible to find people by convenience. Just ask for people who fit your sample criteria and see who shows up. Or reach out to friends and colleagues and see if they know anyone that fits. Don’t let the name convenience sampling mislead you; this is not exactly “easy,” and it is certainly a valid form of sampling in qualitative research. The more unknowns you have about what you will find, the more convenience sampling makes sense. If you don’t know how race or class or political affiliation might matter, and your population is unvaccinated college students, you can construct a sample of college students by placing an advertisement in the student paper or posting a flyer on a notice board. Whoever answers is your sample. That is what is meant by a convenience sample. A common variation of convenience sampling is snowball sampling . This is particularly useful if your target population is hard to find. Let’s say you posted a flyer about your study and only two college students responded. You could then ask those two students for referrals. They tell their friends, and those friends tell other friends, and, like a snowball, your sample gets bigger and bigger.

Researcher Note

Gaining Access: When Your Friend Is Your Research Subject

My early experience with qualitative research was rather unique. At that time, I needed to do a project that required me to interview first-generation college students, and my friends, with whom I had been sharing a dorm for two years, just perfectly fell into the sample category. Thus, I just asked them and easily “gained my access” to the research subject; I know them, we are friends, and I am part of them. I am an insider. I also thought, “Well, since I am part of the group, I can easily understand their language and norms, I can capture their honesty, read their nonverbal cues well, will get more information, as they will be more opened to me because they trust me.” All in all, easy access with rich information. But, gosh, I did not realize that my status as an insider came with a price! When structuring the interview questions, I began to realize that rather than focusing on the unique experiences of my friends, I mostly based the questions on my own experiences, assuming we have similar if not the same experiences. I began to struggle with my objectivity and even questioned my role; am I doing this as part of the group or as a researcher? I came to know later that my status as an insider or my “positionality” may impact my research. It not only shapes the process of data collection but might heavily influence my interpretation of the data. I came to realize that although my inside status came with a lot of benefits (especially for access), it could also bring some drawbacks.

—Dede Setiono, PhD student focusing on international development and environmental policy, Oregon State University

The more you know about what you might find, the more strategic you can be. If you wanted to compare how politically conservative and politically liberal college students explained their vaccine hesitancy, for example, you might construct a sample purposively, finding an equal number of both types of students so that you can make those comparisons in your analysis. This is what Damaske ( 2021 ) did. You could still use convenience or snowball sampling as a way of recruitment. Post a flyer at the conservative student club and then ask for referrals from the one student that agrees to be interviewed. As with convenience sampling, there are variations of purposive sampling as well as other names used (e.g., judgment, quota, stratified, criterion, theoretical). Try not to get bogged down in the nomenclature; instead, focus on identifying the general population that matches your research question and then using a sampling method that is most likely to provide insight, given the types of questions you have.

There are all kinds of ways of being strategic with sampling in qualitative research. Here are a few of my favorite techniques for maximizing insight:

Consider using “extreme” or “deviant” cases. Maybe your college houses a prominent anti-vaxxer who has written about and demonstrated against the college’s policy on vaccines. You could learn a lot from that single case (depending on your research question, of course).
Consider “intensity”: people and cases and circumstances where your questions are more likely to feature prominently (but not extremely or deviantly). For example, you could compare those who volunteer at local Republican and Democratic election headquarters during an election season in a study on why party matters. Those who volunteer are more likely to have something to say than those who are more apathetic.
Maximize variation, as with the case of “politically liberal” versus “politically conservative,” or include an array of social locations (young vs. old; Northwest vs. Southeast region). This kind of heterogeneity sampling can capture and describe the central themes that cut across the variations: any common patterns that emerge, even in this wildly mismatched sample, are probably important to note!
Rather than maximize the variation, you could select a small homogenous sample to describe some particular subgroup in depth. Focus groups are often the best form of data collection for homogeneity sampling.
Think about which cases are “critical” or politically important—ones that “if it happens here, it would happen anywhere” or a case that is politically sensitive, as with the single “blue” (Democratic) county in a “red” (Republican) state. In both, you are choosing a site that would yield the most information and have the greatest impact on the development of knowledge.
On the other hand, sometimes you want to select the “typical”—the typical college student, for example. You are trying to not generalize from the typical but illustrate aspects that may be typical of this case or group. When selecting for typicality, be clear with yourself about why the typical matches your research questions (and who might be excluded or marginalized in doing so).
Finally, it is often a good idea to look for disconfirming cases : if you are at the stage where you have a hypothesis (of sorts), you might select those who do not fit your hypothesis—you will surely learn something important there. They may be “exceptions that prove the rule” or exceptions that force you to alter your findings in order to make sense of these additional cases.

In addition to all these sampling variations, there is the theoretical approach taken by grounded theorists in which the researcher samples comparative people (or events) on the basis of their potential to represent important theoretical constructs. The sample, one can say, is by definition representative of the phenomenon of interest. It accompanies the constant comparative method of analysis. In the words of the funders of Grounded Theory , “Theoretical sampling is sampling on the basis of the emerging concepts, with the aim being to explore the dimensional range or varied conditions along which the properties of the concepts vary” ( Strauss and Corbin 1998:73 ).

When Your Population is Not Composed of People

I think it is easiest for most people to think of populations and samples in terms of people, but sometimes our units of analysis are not actually people. They could be places or institutions. Even so, you might still want to talk to people or observe the actions of people to understand those places or institutions. Or not! In the case of content analyses (see chapter 17), you won’t even have people involved at all but rather documents or films or photographs or news clippings. Everything we have covered about sampling applies to other units of analysis too. Let’s work through some examples.

Case Studies

When constructing a case study, it is helpful to think of your cases as sample populations in the same way that we considered people above. If, for example, you are comparing campus climates for diversity, your overall population may be “four-year college campuses in the US,” and from there you might decide to study three college campuses as your sample. Which three? Will you use purposeful sampling (perhaps [1] selecting three colleges in Oregon that are different sizes or [2] selecting three colleges across the US located in different political cultures or [3] varying the three colleges by racial makeup of the student body)? Or will you select three colleges at random, out of convenience? There are justifiable reasons for all approaches.

As with people, there are different ways of maximizing insight in your sample selection. Think about the following rationales: typical, diverse, extreme, deviant, influential, crucial, or even embodying a particular “pathway” ( Gerring 2008 ). When choosing a case or particular research site, Rubin ( 2021 ) suggests you bear in mind, first, what you are leaving out by selecting this particular case/site; second, what you might be overemphasizing by studying this case/site and not another; and, finally, whether you truly need to worry about either of those things—“that is, what are the sources of bias and how bad are they for what you are trying to do?” ( 89 ).

Once you have selected your cases, you may still want to include interviews with specific people or observations at particular sites within those cases. Then you go through possible sampling approaches all over again to determine which people will be contacted.

Content: Documents, Narrative Accounts, And So On

Although not often discussed as sampling, your selection of documents and other units to use in various content/historical analyses is subject to similar considerations. When you are asking quantitative-type questions (percentages and proportionalities of a general population), you will want to follow probabilistic sampling. For example, I created a random sample of accounts posted on the website studentloanjustice.org to delineate the types of problems people were having with student debt ( Hurst 2007 ). Even though my data was qualitative (narratives of student debt), I was actually asking a quantitative-type research question, so it was important that my sample was representative of the larger population (debtors who posted on the website). On the other hand, when you are asking qualitative-type questions, the selection process should be very different. In that case, use nonprobabilistic techniques, either convenience (where you are really new to this data and do not have the ability to set comparative criteria or even know what a deviant case would be) or some variant of purposive sampling. Let’s say you were interested in the visual representation of women in media published in the 1950s. You could select a national magazine like Time for a “typical” representation (and for its convenience, as all issues are freely available on the web and easy to search). Or you could compare one magazine known for its feminist content versus one antifeminist. The point is, sample selection is important even when you are not interviewing or observing people.

Goals of Qualitative Sampling versus Goals of Quantitative Sampling

We have already discussed some of the differences in the goals of quantitative and qualitative sampling above, but it is worth further discussion. The quantitative researcher seeks a sample that is representative of the population of interest so that they may properly generalize the results (e.g., if 80 percent of first-gen students in the sample were concerned with costs of college, then we can say there is a strong likelihood that 80 percent of first-gen students nationally are concerned with costs of college). The qualitative researcher does not seek to generalize in this way . They may want a representative sample because they are interested in typical responses or behaviors of the population of interest, but they may very well not want a representative sample at all. They might want an “extreme” or deviant case to highlight what could go wrong with a particular situation, or maybe they want to examine just one case as a way of understanding what elements might be of interest in further research. When thinking of your sample, you will have to know why you are selecting the units, and this relates back to your research question or sets of questions. It has nothing to do with having a representative sample to generalize results. You may be tempted—or it may be suggested to you by a quantitatively minded member of your committee—to create as large and representative a sample as you possibly can to earn credibility from quantitative researchers. Ignore this temptation or suggestion. The only thing you should be considering is what sample will best bring insight into the questions guiding your research. This has implications for the number of people (or units) in your study as well, which is the topic of the next section.

What is the Correct “Number” to Sample?

Because we are not trying to create a generalizable representative sample, the guidelines for the “number” of people to interview or news stories to code are also a bit more nebulous. There are some brilliant insightful studies out there with an n of 1 (meaning one person or one account used as the entire set of data). This is particularly so in the case of autoethnography, a variation of ethnographic research that uses the researcher’s own subject position and experiences as the basis of data collection and analysis. But it is true for all forms of qualitative research. There are no hard-and-fast rules here. The number to include is what is relevant and insightful to your particular study.

That said, humans do not thrive well under such ambiguity, and there are a few helpful suggestions that can be made. First, many qualitative researchers talk about “saturation” as the end point for data collection. You stop adding participants when you are no longer getting any new information (or so very little that the cost of adding another interview subject or spending another day in the field exceeds any likely benefits to the research). The term saturation was first used here by Glaser and Strauss ( 1967 ), the founders of Grounded Theory. Here is their explanation: “The criterion for judging when to stop sampling the different groups pertinent to a category is the category’s theoretical saturation . Saturation means that no additional data are being found whereby the sociologist can develop properties of the category. As he [or she] sees similar instances over and over again, the researcher becomes empirically confident that a category is saturated. [They go] out of [their] way to look for groups that stretch diversity of data as far as possible, just to make certain that saturation is based on the widest possible range of data on the category” ( 61 ).

It makes sense that the term was developed by grounded theorists, since this approach is rather more open-ended than other approaches used by qualitative researchers. With so much left open, having a guideline of “stop collecting data when you don’t find anything new” is reasonable. However, saturation can’t help much when first setting out your sample. How do you know how many people to contact to interview? What number will you put down in your institutional review board (IRB) protocol (see chapter 8)? You may guess how many people or units it will take to reach saturation, but there really is no way to know in advance. The best you can do is think about your population and your questions and look at what others have done with similar populations and questions.

Here are some suggestions to use as a starting point: For phenomenological studies, try to interview at least ten people for each major category or group of people . If you are comparing male-identified, female-identified, and gender-neutral college students in a study on gender regimes in social clubs, that means you might want to design a sample of thirty students, ten from each group. This is the minimum suggested number. Damaske’s ( 2021 ) sample of one hundred allows room for up to twenty-five participants in each of four “buckets” (e.g., working-class*female, working-class*male, middle-class*female, middle-class*male). If there is more than one comparative group (e.g., you are comparing students attending three different colleges, and you are comparing White and Black students in each), you can sometimes reduce the number for each group in your sample to five for, in this case, thirty total students. But that is really a bare minimum you will want to go. A lot of people will not trust you with only “five” cases in a bucket. Lareau ( 2021:24 ) advises a minimum of seven or nine for each bucket (or “cell,” in her words). The point is to think about what your analyses might look like and how comfortable you will be with a certain number of persons fitting each category.

Because qualitative research takes so much time and effort, it is rare for a beginning researcher to include more than thirty to fifty people or units in the study. You may not be able to conduct all the comparisons you might want simply because you cannot manage a larger sample. In that case, the limits of who you can reach or what you can include may influence you to rethink an original overcomplicated research design. Rather than include students from every racial group on a campus, for example, you might want to sample strategically, thinking about the most contrast (insightful), possibly excluding majority-race (White) students entirely, and simply using previous literature to fill in gaps in our understanding. For example, one of my former students was interested in discovering how race and class worked at a predominantly White institution (PWI). Due to time constraints, she simplified her study from an original sample frame of middle-class and working-class domestic Black and international African students (four buckets) to a sample frame of domestic Black and international African students (two buckets), allowing the complexities of class to come through individual accounts rather than from part of the sample frame. She wisely decided not to include White students in the sample, as her focus was on how minoritized students navigated the PWI. She was able to successfully complete her project and develop insights from the data with fewer than twenty interviewees. [1]

But what if you had unlimited time and resources? Would it always be better to interview more people or include more accounts, documents, and units of analysis? No! Your sample size should reflect your research question and the goals you have set yourself. Larger numbers can sometimes work against your goals. If, for example, you want to help bring out individual stories of success against the odds, adding more people to the analysis can end up drowning out those individual stories. Sometimes, the perfect size really is one (or three, or five). It really depends on what you are trying to discover and achieve in your study. Furthermore, studies of one hundred or more (people, documents, accounts, etc.) can sometimes be mistaken for quantitative research. Inevitably, the large sample size will push the researcher into simplifying the data numerically. And readers will begin to expect generalizability from such a large sample.

To summarize, “There are no rules for sample size in qualitative inquiry. Sample size depends on what you want to know, the purpose of the inquiry, what’s at stake, what will be useful, what will have credibility, and what can be done with available time and resources” ( Patton 2002:244 ).

How did you find/construct a sample?

Since qualitative researchers work with comparatively small sample sizes, getting your sample right is rather important. Yet it is also difficult to accomplish. For instance, a key question you need to ask yourself is whether you want a homogeneous or heterogeneous sample. In other words, do you want to include people in your study who are by and large the same, or do you want to have diversity in your sample?

For many years, I have studied the experiences of students who were the first in their families to attend university. There is a rather large number of sampling decisions I need to consider before starting the study. (1) Should I only talk to first-in-family students, or should I have a comparison group of students who are not first-in-family? (2) Do I need to strive for a gender distribution that matches undergraduate enrollment patterns? (3) Should I include participants that reflect diversity in gender identity and sexuality? (4) How about racial diversity? First-in-family status is strongly related to some ethnic or racial identity. (5) And how about areas of study?

As you can see, if I wanted to accommodate all these differences and get enough study participants in each category, I would quickly end up with a sample size of hundreds, which is not feasible in most qualitative research. In the end, for me, the most important decision was to maximize the voices of first-in-family students, which meant that I only included them in my sample. As for the other categories, I figured it was going to be hard enough to find first-in-family students, so I started recruiting with an open mind and an understanding that I may have to accept a lack of gender, sexuality, or racial diversity and then not be able to say anything about these issues. But I would definitely be able to speak about the experiences of being first-in-family.

—Wolfgang Lehmann, author of “Habitus Transformation and Hidden Injuries”

Examples of “Sample” Sections in Journal Articles

Think about some of the studies you have read in college, especially those with rich stories and accounts about people’s lives. Do you know how the people were selected to be the focus of those stories? If the account was published by an academic press (e.g., University of California Press or Princeton University Press) or in an academic journal, chances are that the author included a description of their sample selection. You can usually find these in a methodological appendix (book) or a section on “research methods” (article).

Here are two examples from recent books and one example from a recent article:

Example 1 . In It’s Not like I’m Poor: How Working Families Make Ends Meet in a Post-welfare World , the research team employed a mixed methods approach to understand how parents use the earned income tax credit, a refundable tax credit designed to provide relief for low- to moderate-income working people ( Halpern-Meekin et al. 2015 ). At the end of their book, their first appendix is “Introduction to Boston and the Research Project.” After describing the context of the study, they include the following description of their sample selection:

In June 2007, we drew 120 names at random from the roughly 332 surveys we gathered between February and April. Within each racial and ethnic group, we aimed for one-third married couples with children and two-thirds unmarried parents. We sent each of these families a letter informing them of the opportunity to participate in the in-depth portion of our study and then began calling the home and cell phone numbers they provided us on the surveys and knocking on the doors of the addresses they provided.…In the end, we interviewed 115 of the 120 families originally selected for the in-depth interview sample (the remaining five families declined to participate). ( 22 )

Was their sample selection based on convenience or purpose? Why do you think it was important for them to tell you that five families declined to be interviewed? There is actually a trick here, as the names were pulled randomly from a survey whose sample design was probabilistic. Why is this important to know? What can we say about the representativeness or the uniqueness of whatever findings are reported here?

Example 2 . In When Diversity Drops , Park ( 2013 ) examines the impact of decreasing campus diversity on the lives of college students. She does this through a case study of one student club, the InterVarsity Christian Fellowship (IVCF), at one university (“California University,” a pseudonym). Here is her description:

I supplemented participant observation with individual in-depth interviews with sixty IVCF associates, including thirty-four current students, eight former and current staff members, eleven alumni, and seven regional or national staff members. The racial/ethnic breakdown was twenty-five Asian Americans (41.6 percent), one Armenian (1.6 percent), twelve people who were black (20.0 percent), eight Latino/as (13.3 percent), three South Asian Americans (5.0 percent), and eleven people who were white (18.3 percent). Twenty-nine were men, and thirty-one were women. Looking back, I note that the higher number of Asian Americans reflected both the group’s racial/ethnic composition and my relative ease about approaching them for interviews. ( 156 )

How can you tell this is a convenience sample? What else do you note about the sample selection from this description?

Example 3. The last example is taken from an article published in the journal Research in Higher Education . Published articles tend to be more formal than books, at least when it comes to the presentation of qualitative research. In this article, Lawson ( 2021 ) is seeking to understand why female-identified college students drop out of majors that are dominated by male-identified students (e.g., engineering, computer science, music theory). Here is the entire relevant section of the article:

Method Participants Data were collected as part of a larger study designed to better understand the daily experiences of women in MDMs [male-dominated majors].…Participants included 120 students from a midsize, Midwestern University. This sample included 40 women and 40 men from MDMs—defined as any major where at least 2/3 of students are men at both the university and nationally—and 40 women from GNMs—defined as any may where 40–60% of students are women at both the university and nationally.… Procedure A multi-faceted approach was used to recruit participants; participants were sent targeted emails (obtained based on participants’ reported gender and major listings), campus-wide emails sent through the University’s Communication Center, flyers, and in-class presentations. Recruitment materials stated that the research focused on the daily experiences of college students, including classroom experiences, stressors, positive experiences, departmental contexts, and career aspirations. Interested participants were directed to email the study coordinator to verify eligibility (at least 18 years old, man/woman in MDM or woman in GNM, access to a smartphone). Sixteen interested individuals were not eligible for the study due to the gender/major combination. ( 482ff .)

What method of sample selection was used by Lawson? Why is it important to define “MDM” at the outset? How does this definition relate to sampling? Why were interested participants directed to the study coordinator to verify eligibility?

Final Words

I have found that students often find it difficult to be specific enough when defining and choosing their sample. It might help to think about your sample design and sample recruitment like a cookbook. You want all the details there so that someone else can pick up your study and conduct it as you intended. That person could be yourself, but this analogy might work better if you have someone else in mind. When I am writing down recipes, I often think of my sister and try to convey the details she would need to duplicate the dish. We share a grandmother whose recipes are full of handwritten notes in the margins, in spidery ink, that tell us what bowl to use when or where things could go wrong. Describe your sample clearly, convey the steps required accurately, and then add any other details that will help keep you on track and remind you why you have chosen to limit possible interviewees to those of a certain age or class or location. Imagine actually going out and getting your sample (making your dish). Do you have all the necessary details to get started?

Table 5.1. Sampling Type and Strategies

Chapter 5 Research Design

Research design is a comprehensive plan for data collection in an empirical research project. It is a “blueprint” for empirical research aimed at answering specific research questions or testing specific hypotheses, and must specify at least three processes: (1) the data collection process, (2) the instrument development process, and (3) the sampling process. The instrument development and sampling processes are described in next two chapters, and the data collection process (which is often loosely called “research design”) is introduced in this chapter and is described in further detail in Chapters 9-12.

Broadly speaking, data collection methods can be broadly grouped into two categories: positivist and interpretive. Positivist methods , such as laboratory experiments and survey research, are aimed at theory (or hypotheses) testing, while interpretive methods, such as action research and ethnography, are aimed at theory building. Positivist methods employ a deductive approach to research, starting with a theory and testing theoretical postulates using empirical data. In contrast, interpretive methods employ an inductive approach that starts with data and tries to derive a theory about the phenomenon of interest from the observed data. Often times, these methods are incorrectly equated with quantitative and qualitative research. Quantitative and qualitative methods refers to the type of data being collected (quantitative data involve numeric scores, metrics, and so on, while qualitative data includes interviews, observations, and so forth) and analyzed (i.e., using quantitative techniques such as regression or qualitative techniques such as coding). Positivist research uses predominantly quantitative data, but can also use qualitative data. Interpretive research relies heavily on qualitative data, but can sometimes benefit from including quantitative data as well. Sometimes, joint use of qualitative and quantitative data may help generate unique insight into a complex social phenomenon that are not available from either types of data alone, and hence, mixed-mode designs that combine qualitative and quantitative data are often highly desirable.

Key Attributes of a Research Design

The quality of research designs can be defined in terms of four key design attributes: internal validity, external validity, construct validity, and statistical conclusion validity.

Internal validity , also called causality, examines whether the observed change in a dependent variable is indeed caused by a corresponding change in hypothesized independent variable, and not by variables extraneous to the research context. Causality requires three conditions: (1) covariation of cause and effect (i.e., if cause happens, then effect also happens; and if cause does not happen, effect does not happen), (2) temporal precedence: cause must precede effect in time, (3) no plausible alternative explanation (or spurious correlation). Certain research designs, such as laboratory experiments, are strong in internal validity by virtue of their ability to manipulate the independent variable (cause) via a treatment and observe the effect (dependent variable) of that treatment after a certain point in time, while controlling for the effects of extraneous variables. Other designs, such as field surveys, are poor in internal validity because of their inability to manipulate the independent variable (cause), and because cause and effect are measured at the same point in time which defeats temporal precedence making it equally likely that the expected effect might have influenced the expected cause rather than the reverse. Although higher in internal validity compared to other methods, laboratory experiments are, by no means, immune to threats of internal validity, and are susceptible to history, testing, instrumentation, regression, and other threats that are discussed later in the chapter on experimental designs. Nonetheless, different research designs vary considerably in their respective level of internal validity.

External validity or generalizability refers to whether the observed associations can be generalized from the sample to the population (population validity), or to other people, organizations, contexts, or time (ecological validity). For instance, can results drawn from a sample of financial firms in the United States be generalized to the population of financial firms (population validity) or to other firms within the United States (ecological validity)? Survey research, where data is sourced from a wide variety of individuals, firms, or other units of analysis, tends to have broader generalizability than laboratory experiments where artificially contrived treatments and strong control over extraneous variables render the findings less generalizable to real-life settings where treatments and extraneous variables cannot be controlled. The variation in internal and external validity for a wide range of research designs are shown in Figure 5.1.

Figure 5.1. Internal and external validity.

Some researchers claim that there is a tradeoff between internal and external validity: higher external validity can come only at the cost of internal validity and vice-versa. But this is not always the case. Research designs such as field experiments, longitudinal field surveys, and multiple case studies have higher degrees of both internal and external validities. Personally, I prefer research designs that have reasonable degrees of both internal and external validities, i.e., those that fall within the cone of validity shown in Figure 5.1. But this should not suggest that designs outside this cone are any less useful or valuable. Researchers’ choice of designs is ultimately a matter of their personal preference and competence, and the level of internal and external validity they desire.

Construct validity examines how well a given measurement scale is measuring the theoretical construct that it is expected to measure. Many constructs used in social science research such as empathy, resistance to change, and organizational learning are difficult to define, much less measure. For instance, construct validity must assure that a measure of empathy is indeed measuring empathy and not compassion, which may be difficult since these constructs are somewhat similar in meaning. Construct validity is assessed in positivist research based on correlational or factor analysis of pilot test data, as described in the next chapter.

Statistical conclusion validity examines the extent to which conclusions derived using a statistical procedure is valid. For example, it examines whether the right statistical method was used for hypotheses testing, whether the variables used meet the assumptions of that statistical test (such as sample size or distributional requirements), and so forth. Because interpretive research designs do not employ statistical test, statistical conclusion validity is not applicable for such analysis. The different kinds of validity and where they exist at the theoretical/empirical levels are illustrated in Figure 5.2.

Figure 5.2. Different Types of Validity in Scientific Research

Improving Internal and External Validity

The best research designs are those that can assure high levels of internal and external validity. Such designs would guard against spurious correlations, inspire greater faith in the hypotheses testing, and ensure that the results drawn from a small sample are generalizable to the population at large. Controls are required to assure internal validity (causality) of research designs, and can be accomplished in four ways: (1) manipulation, (2) elimination, (3) inclusion, and (4) statistical control, and (5) randomization.

In manipulation , the researcher manipulates the independent variables in one or more levels (called “treatments”), and compares the effects of the treatments against a control group where subjects do not receive the treatment. Treatments may include a new drug or different dosage of drug (for treating a medical condition), a, a teaching style (for students), and so forth. This type of control is achieved in experimental or quasi-experimental designs but not in non-experimental designs such as surveys. Note that if subjects cannot distinguish adequately between different levels of treatment manipulations, their responses across treatments may not be different, and manipulation would fail.

The elimination technique relies on eliminating extraneous variables by holding them constant across treatments, such as by restricting the study to a single gender or a single socio-economic status. In the inclusion technique, the role of extraneous variables is considered by including them in the research design and separately estimating their effects on the dependent variable, such as via factorial designs where one factor is gender (male versus female). Such technique allows for greater generalizability but also requires substantially larger samples. In statistical control , extraneous variables are measured and used as covariates during the statistical testing process.

Finally, the randomization technique is aimed at canceling out the effects of extraneous variables through a process of random sampling, if it can be assured that these effects are of a random (non-systematic) nature. Two types of randomization are: (1) random selection , where a sample is selected randomly from a population, and (2) random assignment , where subjects selected in a non-random manner are randomly assigned to treatment groups.

Randomization also assures external validity, allowing inferences drawn from the sample to be generalized to the population from which the sample is drawn. Note that random assignment is mandatory when random selection is not possible because of resource or access constraints. However, generalizability across populations is harder to ascertain since populations may differ on multiple dimensions and you can only control for few of those dimensions.

Popular Research Designs

As noted earlier, research designs can be classified into two categories – positivist and interpretive – depending how their goal in scientific research. Positivist designs are meant for theory testing, while interpretive designs are meant for theory building. Positivist designs seek generalized patterns based on an objective view of reality, while interpretive designs seek subjective interpretations of social phenomena from the perspectives of the subjects involved. Some popular examples of positivist designs include laboratory experiments, field experiments, field surveys, secondary data analysis, and case research while examples of interpretive designs include case research, phenomenology, and ethnography. Note that case research can be used for theory building or theory testing, though not at the same time. Not all techniques are suited for all kinds of scientific research. Some techniques such as focus groups are best suited for exploratory research, others such as ethnography are best for descriptive research, and still others such as laboratory experiments are ideal for explanatory research. Following are brief descriptions of some of these designs. Additional details are provided in Chapters 9-12.

Experimental studies are those that are intended to test cause-effect relationships (hypotheses) in a tightly controlled setting by separating the cause from the effect in time, administering the cause to one group of subjects (the “treatment group”) but not to another group (“control group”), and observing how the mean effects vary between subjects in these two groups. For instance, if we design a laboratory experiment to test the efficacy of a new drug in treating a certain ailment, we can get a random sample of people afflicted with that ailment, randomly assign them to one of two groups (treatment and control groups), administer the drug to subjects in the treatment group, but only give a placebo (e.g., a sugar pill with no medicinal value). More complex designs may include multiple treatment groups, such as low versus high dosage of the drug, multiple treatments, such as combining drug administration with dietary interventions. In a true experimental design , subjects must be randomly assigned between each group. If random assignment is not followed, then the design becomes quasi-experimental . Experiments can be conducted in an artificial or laboratory setting such as at a university (laboratory experiments) or in field settings such as in an organization where the phenomenon of interest is actually occurring (field experiments). Laboratory experiments allow the researcher to isolate the variables of interest and control for extraneous variables, which may not be possible in field experiments. Hence, inferences drawn from laboratory experiments tend to be stronger in internal validity, but those from field experiments tend to be stronger in external validity. Experimental data is analyzed using quantitative statistical techniques. The primary strength of the experimental design is its strong internal validity due to its ability to isolate, control, and intensively examine a small number of variables, while its primary weakness is limited external generalizability since real life is often more complex (i.e., involve more extraneous variables) than contrived lab settings. Furthermore, if the research does not identify ex ante relevant extraneous variables and control for such variables, such lack of controls may hurt internal validity and may lead to spurious correlations.

Field surveys are non-experimental designs that do not control for or manipulate independent variables or treatments, but measure these variables and test their effects using statistical methods. Field surveys capture snapshots of practices, beliefs, or situations from a random sample of subjects in field settings through a survey questionnaire or less frequently, through a structured interview. In cross-sectional field surveys , independent and dependent variables are measured at the same point in time (e.g., using a single questionnaire), while in longitudinal field surveys , dependent variables are measured at a later point in time than the independent variables. The strengths of field surveys are their external validity (since data is collected in field settings), their ability to capture and control for a large number of variables, and their ability to study a problem from multiple perspectives or using multiple theories. However, because of their non-temporal nature, internal validity (cause-effect relationships) are difficult to infer, and surveys may be subject to respondent biases (e.g., subjects may provide a “socially desirable” response rather than their true response) which further hurts internal validity.

Secondary data analysis is an analysis of data that has previously been collected and tabulated by other sources. Such data may include data from government agencies such as employment statistics from the U.S. Bureau of Labor Services or development statistics by country from the United Nations Development Program, data collected by other researchers (often used in meta-analytic studies), or publicly available third-party data, such as financial data from stock markets or real-time auction data from eBay. This is in contrast to most other research designs where collecting primary data for research is part of the researcher’s job.

Secondary data analysis may be an effective means of research where primary data collection is too costly or infeasible, and secondary data is available at a level of analysis suitable for answering the researcher’s questions. The limitations of this design are that the data might not have been collected in a systematic or scientific manner and hence unsuitable for scientific research, since the data was collected for a presumably different purpose, they may not adequately address the research questions of interest to the researcher, and interval validity is problematic if the temporal precedence between cause and effect is unclear.

Case research is an in-depth investigation of a problem in one or more real-life settings (case sites) over an extended period of time. Data may be collected using a combination of interviews, personal observations, and internal or external documents. Case studies can be positivist in nature (for hypotheses testing) or interpretive (for theory building). The strength of this research method is its ability to discover a wide variety of social, cultural, and political factors potentially related to the phenomenon of interest that may not be known in advance. Analysis tends to be qualitative in nature, but heavily contextualized and nuanced. However, interpretation of findings may depend on the observational and integrative ability of the researcher, lack of control may make it difficult to establish causality, and findings from a single case site may not be readily generalized to other case sites. Generalizability can be improved by replicating and comparing the analysis in other case sites in a multiple case design .

Focus group research is a type of research that involves bringing in a small group of subjects (typically 6 to 10 people) at one location, and having them discuss a phenomenon of interest for a period of 1.5 to 2 hours. The discussion is moderated and led by a trained facilitator, who sets the agenda and poses an initial set of questions for participants, makes sure that ideas and experiences of all participants are represented, and attempts to build a holistic understanding of the problem situation based on participants’ comments and experiences.

Internal validity cannot be established due to lack of controls and the findings may not be generalized to other settings because of small sample size. Hence, focus groups are not generally used for explanatory or descriptive research, but are more suited for exploratory research.

Action research assumes that complex social phenomena are best understood by introducing interventions or “actions” into those phenomena and observing the effects of those actions. In this method, the researcher is usually a consultant or an organizational member embedded within a social context such as an organization, who initiates an action such as new organizational procedures or new technologies, in response to a real problem such as declining profitability or operational bottlenecks. The researcher’s choice of actions must be based on theory, which should explain why and how such actions may cause the desired change. The researcher then observes the results of that action, modifying it as necessary, while simultaneously learning from the action and generating theoretical insights about the target problem and interventions. The initial theory is validated by the extent to which the chosen action successfully solves the target problem. Simultaneous problem solving and insight generation is the central feature that distinguishes action research from all other research methods, and hence, action research is an excellent method for bridging research and practice. This method is also suited for studying unique social problems that cannot be replicated outside that context, but it is also subject to researcher bias and subjectivity, and the generalizability of findings is often restricted to the context where the study was conducted.

Ethnography is an interpretive research design inspired by anthropology that emphasizes that research phenomenon must be studied within the context of its culture. The researcher is deeply immersed in a certain culture over an extended period of time (8 months to 2 years), and during that period, engages, observes, and records the daily life of the studied culture, and theorizes about the evolution and behaviors in that culture. Data is collected primarily via observational techniques, formal and informal interaction with participants in that culture, and personal field notes, while data analysis involves “sense-making”. The researcher must narrate her experience in great detail so that readers may experience that same culture without necessarily being there. The advantages of this approach are its sensitiveness to the context, the rich and nuanced understanding it generates, and minimal respondent bias. However, this is also an extremely time and resource-intensive approach, and findings are specific to a given culture and less generalizable to other cultures.

Selecting Research Designs

Given the above multitude of research designs, which design should researchers choose for their research? Generally speaking, researchers tend to select those research designs that they are most comfortable with and feel most competent to handle, but ideally, the choice should depend on the nature of the research phenomenon being studied. In the preliminary phases of research, when the research problem is unclear and the researcher wants to scope out the nature and extent of a certain research problem, a focus group (for individual unit of analysis) or a case study (for organizational unit of analysis) is an ideal strategy for exploratory research. As one delves further into the research domain, but finds that there are no good theories to explain the phenomenon of interest and wants to build a theory to fill in the unmet gap in that area, interpretive designs such as case research or ethnography may be useful designs. If competing theories exist and the researcher wishes to test these different theories or integrate them into a larger theory, positivist designs such as experimental design, survey research, or secondary data analysis are more appropriate.

Regardless of the specific research design chosen, the researcher should strive to collect quantitative and qualitative data using a combination of techniques such as questionnaires, interviews, observations, documents, or secondary data. For instance, even in a highly structured survey questionnaire, intended to collect quantitative data, the researcher may leave some room for a few open-ended questions to collect qualitative data that may generate unexpected insights not otherwise available from structured quantitative data alone. Likewise, while case research employ mostly face-to-face interviews to collect most qualitative data, the potential and value of collecting quantitative data should not be ignored. As an example, in a study of organizational decision making processes, the case interviewer can record numeric quantities such as how many months it took to make certain organizational decisions, how many people were involved in that decision process, and how many decision alternatives were considered, which can provide valuable insights not otherwise available from interviewees’ narrative responses. Irrespective of the specific research design employed, the goal of the researcher should be to collect as much and as diverse data as possible that can help generate the best possible insights about the phenomenon of interest.

Social Science Research: Principles, Methods, and Practices. Authored by : Anol Bhattacherjee. Provided by : University of South Florida. Located at : http://scholarcommons.usf.edu/oa_textbooks/3/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

Chapter Five: Qualitative Methods (Part 1)

Every day you are confronted with the need to understand research methodology. In your work life, you are asked to compile and process data. Whether you are researching leadership techniques or analyzing sales statistics, you must be able to interpret the data you encounter. There is an everyday utility to qualitative techniques such as observation or interviewing. Imagine yourself as a new member of an organization. What are the informal rules of the organization? What is the culture of this work environment? Are there expectations other than the ones provided in the job description or by the supervisor? Over time, with keen observation and interview skills, a new organization member can uncover the answers to these and other questions. So, while the information contained in this section approaches qualitative methodologies from a scholarly perspective, the skills and techniques identified herein will help you understand human social action in a variety of situations.

Chapter One: Introduction
Chapter Two: Understanding the distinctions among research methods
Chapter Three: Ethical research, writing, and creative work
Chapter Four: Quantitative Methods (Part 1)
Chapter Four: Quantitative Methods (Part 2 - Doing Your Study)
Chapter Four: Quantitative Methods (Part 3 - Making Sense of Your Study)
Chapter Five: Qualitative Data (Part 2)
Chapter Six: Critical / Rhetorical Methods (Part 1)
Chapter Six: Critical / Rhetorical Methods (Part 2)
Chapter Seven: Presenting Your Results

One of the goals of quantitative research is to produce generalized knowledge about a communication event or phenomenon. Quantitative researchers ground their investigations in the scientific method in order to control or manipulate variables, reduce or eliminate researcher bias, and discover verifiable patterns of human behavior. The goals of quantitative research are to explain, predict, and control behavior. Qualitative research, in contrast, seeks to develop subjective understanding of communication phenomena. Rather than the experimental designs and survey instruments of quantitative researchers, qualitative researchers often seek to collect data in natural settings and rely on observations of and interviews with research participants to create data, which is not designed to produce quantifiable and generalizable results, but rather to produce in-depth understanding specific to particular situations. Although noticeably different from quantitative and rhetorical research designs, qualitative research methods are a popular and vital approach to the identification, understanding, and analysis of human interaction. In this chapter, we discuss the fundamental assumptions, philosophical traditions and salient attributes of qualitative research.

The Qualitative Worldview

Individuals engaged in qualitative research approach their projects from a different perspective than quantitative and rhetorical researchers. Even though all researchers share an interest in accurately reflecting social reality and in crafting an intellectual argument that is built on the foundations of valid data collection and observation, several assumptions are specific to qualitative research. Understanding these assumptions can help you better determine whether you need to use qualitative methods for the particular study in which you are interested.

Assumptions of Qualitative Research

Our knowledge of social reality is based on subjective interpretation. Qualitative researchers assume that due to our limited perception and our individual experiences, our understanding of social reality is necessarily subjective. Due to this, qualitative researchers reject the realist worldview that postulates an objective, measurable reality. Instead, reality is a social construction, given life through intersubjective agreement – that is, the contours of reality are defined by general agreement between humans in the society. Another way to think of this is that reality isn't completely objective – existing externally from humans, but subjective – existing in the interpretations of humans. Concepts such as love, democracy, and friendship are difficult to quantify, and are often the result of negotiated understandings between pairs or groups of people. Therefore, for qualitative researchers, it is important to understand how individuals and groups subjectively understand their experiences.

Subjectivity, in regards to qualitative research, manifests itself in two ways. On one hand, there is the recognition that the participants in the research have their own unique way of interpreting and understanding events and their own social actions. For example, a researcher studying leadership would recognize that research participants, whether they are CEOs or workers, coaches or players, preachers or congregation members, have their own unique perspective on leadership. In order to fully understand leadership, a qualitative researcher would need to consider all, or at least as many as possible, of the various subjective understandings of leadership.

On the other hand, the researcher recognizes that he or she is the primary data collection instrument, and her or his subjectivity affects the study. Rather than utilizing a survey, specifically designed to reduce bias and maintain objectivity, a qualitative researcher, whether through observation or interviewing, filters all of the data through his or her own understanding. In this way, a qualitative researcher must recognize his or her subjectivity regarding the collection and analysis of data.

Research proceeds inductively . Induction is the process of moving from a series of specific observations to a general conclusion or theory. Unlike quantitative research, which often proceeds deductively from a general premise or theory to specific examples, qualitative research, through the gathering of subjective interpretations, seeks to develop general understanding through the analysis of the collected data.

For example, it is unlikely that qualitative research will begin with a theory, such as Inoculation Theory (a theory concerning how people resist persuasion), and then through experimental or survey designs, seek to validate and support the theory. In fact, it is quite the opposite. Qualitative researchers, interested in how people resist persuasion, might begin by asking participants for accounts of times when they have successfully resisted persuasive attempts. Qualitative researchers deliberately avoid beginning with the conclusion. After collecting these individual accounts from participants, researchers analyze the data in order to identify situational rules that then facilitate understanding of social action.

The goal of qualitative research is understanding . Nineteenth century German philosopher Wilhelm Dilthey (2010), articulating the difference between the natural and the social sciences, stated that the former sought causes and effects while the latter sought verstehen . Simply put, verstehen means understanding. One of the founders of sociology, Max Weber, elaborated on Dilthey’s work and stated that the purpose and method of the social sciences should be verstehen . Weber (1962) believed that it was not possible to fully predict human social action. Therefore, rather than attempting to predict and control human behavior, qualitative social scientists should seek to understand social action. It is important to recognize that human social action varies immensely, and it would be difficult to identify social actions that are likely to be consistent from one person to the next and across a variety of circumstances. For example, humans would have a wide range of responses to an embrace from an acquaintance, an insult, slapstick humor, physical violence, or being ignored.

Researchers emphasize credibility, rather than validity/reliability . Many qualitative researchers use the word credibility rather than validity or reliability. This is not to say that qualitative researchers do not desire validity, but rather to recognize that currently validity and reliability are synonymous with the quantitative approach to research. The use of the term credibility is a deliberate choice and refers to the veracity and accuracy of the data collected. Essentially, qualitative researchers are creating an argument—an argument which claims that the conclusions derived from the qualitative research are an accurate reflection of social reality. For example, if a U.S. Senator were giving a speech, we might ask whether or not the speaker is credible and whether or not the information presented in the speech is credible. In much the same way, we might evaluate qualitative research by asking whether or not the researcher and the argument presented in the research are credible.

Knowledge is created through intersubjective agreement . Qualitative researchers believe that knowledge is built through intersubjective agreement. For example, a researcher investigating friendship development among college students realizes that his or her study is only one piece of the puzzle and that a similar study would likely reveal new elements or focus on different characteristics of friendship. It is through the sharing of this body of knowledge that understanding is built. In fact, it is the very process of how research participants collectively construct multiple understandings in which the researcher is interested. Participants define and construct understanding intersubjectively and researchers document this process, enter their findings into the public record through publication, and then jointly construct meaning with other researchers, other participants, and other publications. Participants then become co-researchers with the researcher. This process results in an intersubjective, rather than an objective, understanding of the social world.

The social setting or context is an important element in understanding any communication interaction . Qualitative researchers believe that context is integral to understanding communication. Research often takes place within the natural setting of the participants. For example, a researcher conducting an ethnography of college wrestling would observe the participants at practice, meetings, and competitions, etc.—paying careful attention to the characteristics of the setting. So, why is the context so important? In the case of a wrestling ethnography, many contextual factors aid our understanding of the group. Is the coach new or a seasoned veteran? Does the program have a stellar reputation or is it struggling for respectability? Does the team have 15 members or 45? Does the program have a state-of-the-art practice facility? All of these distinctions can help facilitate the researcher’s understanding of a group in a way that differs from quantitative research involving a survey of 200 wrestlers.

The values of the researcher cannot be completely separated from the research . Qualitative research is a subjective endeavor. A researcher relies on his or her ability to accurately interpret the available data in order to make a valid argument regarding the phenomena under investigation. Because the researcher is the data collection instrument and the values of the researcher are present during the interpretation, extra effort must be made to ensure that the biases of the researcher do not diminish the quality of the interpretation.

In life, it is obvious that people often see what they want to see. If a politician is giving a speech, it is likely that supporters will interpret elements of the speech in a manner that is entirely different from the way that detractors interpret those same elements. Because of this, it is important that researchers recognize and acknowledge the role that their values play in the interpretation of the data and to ensure that their conclusions are built on fully substantiated and supported claims.

In summary, qualitative assumptions include:

Knowledge of social reality is based on subjective interpretation;
Research proceeds inductively;
The goal of qualitative research is understanding;
Researchers emphasize credibility;
Knowledge is created through intersubjective agreement;
The social setting or context is an important element in understanding any communication interaction; and
The values of the researcher cannot be completely separated from the research.

These assumptions represent the worldview shared by qualitative researchers. Ultimately, decisions regarding methodology rest on the types of questions that the researcher wants to answer. If your goal is to understand a particular communication phenomenon in depth, qualitative methods are a good research choice for you.

The Traditions of Qualitative Research

While quantitative research has the firmly established tradition of the scientific method, qualitative research locates its roots in a variety of philosophical strains. Cultural studies, critical theory, ethnomethodology, and others have all contributed to the theoretical traditions of qualitative methodology. However, the three traditions to be discussed here are hermeneutics, phenomenology, and symbolic interactionism.

Hermeneutics

According to Schwandt (2001), hermeneutics refers “to the art, theory, and philosophy of interpreting the meaning of an object” (p. 115). The “object” under examination can take a variety of forms: a Black-Eyed Peas song, a conversation between friends, a commercial for the latest iPhone, or a Presidential State of the Union Address. Hermeneutists call these objects “texts,” and they serve as the data for a hermeneutic study. The process of interpreting meaning makes hermeneutic analysis so fundamental to qualitative research. This process goes beyond the translation of a text and involves an effort to interpret the text. We are engaged in the process of interpretation every day. For example, lawyers, judges, and politicians are constantly in the process of interpreting laws. An ongoing discussion in the United States is whether or not the Bill of Rights is a “living, breathing document,” thus necessitating new interpretation, or is an unchanging document that means the same today as it did upon its ratification in 1791.

Hermeneutics, or interpretation, as a scholarly practice traces its roots to ancient Greek society. However, it is in the area of biblical scholarship that the more recent foundation of hermeneutics rests. Biblical scholars must not only translate ancient religious documents, but must interpret them for a new time period. For example, during the Protestant Reformation, new interpretations of biblical passages strengthened the Protestant cause while shifting away from Roman Catholic interpretations of the text. This process of interpretation is important because it acknowledges that texts must be reevaluated and re-interpreted in order to ascertain applicability and relevance.

Modern hermeneutics, as developed by Dilthey (2010), Gadamer (1976), and Ricoeur (1981), moved hermeneutic analysis beyond the study of ancient texts to include the range of “texts” that we consider for analysis today. Texts can include a near limitless range of social actions—transcripts from an interview, a movie, Congressional proceedings, a commercial, etc. In order to properly understand a text, the interpreter must have an understanding of not only the text, but of the cultural and historical epoch from which it originates. What do we know about the whole of the text? What do we know about the author or authors of the text? What do we know about the time period in which the text was created? Remember, the charge for a hermeneutic researcher is to interpret the text, and the goal of the hermeneutic researcher is understanding. Scholars in this tradition believe that one cannot fully understand a text until one understands the range of forces involved in the creation of the text. In this tradition, the emphasis is on the relationship among the text, author, context, and the researcher.

Phenomenology

While the centrality of interpretation in hermeneutic scholarship marks an approach that is clearly divergent from quantitative research with its scientific method roots, it is with phenomenology that we see a deliberate rejection of quantitative social science and its focus on an objective, measurable reality. Phenomenologists deny the existence of a reality that exists independent of our perceptions.

Phenomenology originated with the work of Edmund Husserl (1990) as he sought to develop a way of objectively studying subjective experiences. Husserl focused on understanding events or phenomena by understanding how people consciously experience those events or phenomena. Husserl’s form of phenomenology, known as transcendental phenomenology , included carefully cataloguing all of the attributes of an item, such as democracy, and then bracketing, or setting aside, those attributes of democracy that are completely subjective—byproducts of culture and the perceptions of the person conducting the analysis. Therefore, if a researcher wanted to understand a concept such as democracy , he or she would identify all of the essential characteristics of democracy. Husserl would then advocate that those items on our list of essential characteristics of democracy that are culturally situated (for example, there are aspects of current U.S. democracy that differ from how other countries define democracy) be bracketed or set aside. By removing our cultural assumptions from the list through the process of bracketing, we are left with those items that seem universally, rather than contextually, valid—the essential characteristics of democracy.

While Husserl was interested in bracketing out the culturally based characteristics of a phenomenon, his student, Alfred Schutz (1967), found that the cultural variations that manifest in individual interpretation of experiences are the most interesting facets of the phenomenon. Therefore, Schutz’s social phenomenology emphasizes the subjective interpretation of everyday experiences. According to Schutz, these types of localized understandings are represented by people’s values, beliefs, etc. He called these typifications. In summary, while Husserl encouraged us to set aside our biases, Schutz asked us to consider how and why our biases develop.

Phenomenology focuses on intersubjectivity . One way to understand the phenomenological concept of intersubjectivity is to imagine a group of researchers independently studying a previously undiscovered tropical island. One researcher, who is able to study the island via helicopter, is able to chronicle those island characteristics viewable from the air. Another researcher studies the island from a submarine and is able to describe the island characteristics viewable from this undersea vantage point. Finally, a third researcher is able to walk around the island and study it from within, and is able to see the island from a different perspective than either the aerial or nautical researcher. When the three researchers get together to share their findings, they identify those areas where their data overlaps—thereby revealing the essential characteristics of the island and achieving an intersubjective understanding. This does not mean that the observations unique to each researcher are invalid, just that it is never fully possible for others to experience the world in exactly the same manner as someone else and that the process of understanding a phenomenon is a process that is both ongoing and contingent. In distinguishing between the phenomenological approaches of Husserl and Schutz, Husserl would focus on where the researchers overlap, while Schutz would be more interested in the unique observations of each of the researchers.

Stewart and Mickunas (1990), after noting the lack of consensus in defining phenomenology, stated, “one can characterize phenomenological philosophy as centering on the following basic themes: a return to the traditional tasks of philosophy, the search for a philosophy without presuppositions, the intentionality of consciousness, and the refusal of the subject-object dichotomy” (p. 5). In summary, phenomenology contributes to qualitative research with its recognition of subjective experiences and its goal of intersubjective meaning construction. Quantitative researchers use sophisticated surveys as measuring devices. In qualitative research, the researcher is the data collection device.

Symbolic Interactionism

The third tradition influencing modern qualitative scholarship is Symbolic Interactionism. The aim for researchers in this tradition is to ascertain how meaning develops. Humans use symbols (words, phrases, images, nonverbal gestures, etc.) to interact with one another. How is it that people are able to agree on common understandings for these symbols? According to Symbolic Interactionists like Mead and Blumer (1986), the cultural meanings that people attach to symbols develop through their interactions with members of their social network, mediated images in their environment, and social context in a larger sense. Through these shared symbolic understandings, people are able to make sense and interpret their experiences.

Symbolic Interactionism focuses on the interplay among mind, self, and society. Mind includes individual human thoughts, while self considers interaction with others. Society provides the context in which meaning is made possible. What each know, their stock of knowledge, is shaped by their experiences and their interactions within a societal network, and knowledge, in turn, impacts the societal network.

Even though people often successfully share meanings, it is important to remember that meanings are constantly under negotiation. While most might share a collective interpretation of the essential characteristics of a dog, the meanings of other terms, like liberal or conservative , are constantly under negotiation. Your own political orientation, the political orientation of your social group, and the political orientation of your family members all shape your understanding of these terms. Additionally, other factors such as how distinct media outlets define liberal or conservative or how you feel about specific politicians influence and guide how you conceptualize these terms. Over the course of the evolution of Symbolic Interactionism, key components developed to further explain the results of interaction among social groups. Significant symbols and significant others are two examples of essential characteristics of this approach to human social action. Significant symbols are those, that when used, elicit understanding among the social group. For example, others might interpret the use of an image of an eagle or an American flag pin on your lapel as representative of your patriotism. The term significant others refers to those whom most shape a person’s understanding of cultural symbols.

Consider a concept such as corporate branding—where a corporation hopes to build a specific connection between a symbol representing their company and their target audience. For example, Nike wants customers and athletes to immediately connect the swoosh on their logo with quality or performance. However, it is important to remember the roles social groups play in people’s interpretation of significant symbols like the Nike swoosh. Some, due to Nike’s lawsuits, might associate the swoosh with unfair labor practices or poor working conditions. This example serves to further demonstrate that cultural understandings are always contingent.

If one considers that these three philosophical traditions represent the foundation of qualitative research, the individual pillars of the foundation reveal themselves. From hermeneutics comes the centrality of interpretation and the identification of texts (in all their myriad forms) as fundamental elements of scholarly analysis. From phenomenology comes the recognition that everything a person understands about reality is filtered through her or his own individual perceptions and that we should strive for intersubjective understandings of reality. Finally, from symbolic interactionism comes the realization that how people experience reality is shaped by the shared symbolic meanings that arise from their social network, cultural group, or philosophical standpoint. All three of these foundations reject a realist ontology; that is, the idea that there is a single objective reality that we can know independent of our subjective interpretation. Elements from nearly all of the assumptions of qualitative research, interpretation, textual artifacts, subjective understanding, and contextual shaping can be traced back to these pillars.

Attributes of Qualitative Research

Before proceeding to an in-depth examination of specific steps for initiating and conducting a qualitative research project, there are a few general attributes and elements of qualitative research to consider. In this section, the authors discuss the primacy of observation as an essential attribute for a qualitative researcher, the types of questions posed by researchers, the different forms of data common to qualitative research, the varieties of sampling, and ways to improve the accuracy of your qualitative findings.

Observation

Having established the relationship between subjectivity and qualitative research and having established that the qualitative researcher, unlike the quantitative researcher, is the primary data collection instrument, it is necessary to consider one of the primary means of data collection in qualitative research: observation. It is common in qualitative research for researchers to immerse themselves in the social environment under investigation. People naturally engage in the process of observation every day—seeing what the weather is like, paying attention to what friends or professors are saying, or attending a meeting with a campus organization. However, systematic, scholarly observation differs from casual observation.

One way to think of how qualitative observation differs from casual observation is to consider playing a game of Texas Hold ‘Em poker. When you get together and play with your friends for skittles or peanuts, you may or may not pay enough attention to see if your opponents are bluffing. Now imagine that you are playing Texas Hold ‘Em on ESPN for ten million dollars. Under those circumstances it is critical that players are able to read the behaviors of others and also have a high awareness of their own behaviors. This is similar to the characteristics of a scholarly observer. When conducting observations for research purposes, researchers need to be able to sort through, process, and accurately capture the variety of stimuli occurring simultaneously in the environment. Additionally, researchers need to be cognizant of their own interpersonal behaviors and consider how they are impacting those in the environment.

Observation plays a very specific role in ethnography, which is when the researcher immerses him or herself into the culture or group being investigated. It also takes a keen eye for observation when conducting focus groups or interviews. Oftentimes, during the early stages of a research project, the researcher might rely on observation to get a preliminary sense of the communication context of the research participants. In general, the observation continuum looks like this:

While the explanation of each type of observation is fairly straightforward, it is worth exploring how each differs from the other. When a researcher takes on the role of complete observer , he or she is usually not already a member of the group under observation. When we study a group as an outsider, we call this adopting an etic perspective . Simply put, it would be difficult to carry out our day-to-day responsibilities as a group member and focus extensively on capturing detailed notes of our observations of the group. Consider a student on the campus of who is having difficulty understanding why the student organization in which he or she is a member (e.g., the Chess Club) is having trouble functioning effectively. This student might identify successful student organizations with the intent of sitting in as an observer in order to try to determine what those groups do that contributes to their success. The student might select a public relations student organization and attend several meetings, not with the intention of joining, but with the intention of identifying the social actions that help make the PR group a successful organization. By carefully and successfully documenting the procedures and activities of the public relations organization, the observer might be able to integrate these behaviors into her or his own organization.

On the other side of the continuum is the complete participant , someone who is already a member of the organization that he or she wants to study. Imagine again that you are the president of the Chess Club, and you want to improve the functioning of your student organization. Because you are the president and have all of the responsibilities associated with that position, it would be very difficult to take time off from your regular duties to take extensive field notes about the Chess Club’s organizational procedures. When you study an organization from an insider’s perspective, as you are in this example, it is called taking an emic perspective . In this case, the complete participant wants to carry out his or her routine responsibilities and then, after the meeting, attempt to write detailed notes describing the activities and experiences of the meeting.

Before discussing the two perspectives that mark the middle areas of the continuum, it is necessary to highlight three salient points regarding differences between taking an etic perspective or an emic perspective.

Although complete observers may bring a fresh set of eyes and be able to focus exclusively on the act of observing, they may find that access is limited and acceptance of their presence is not guaranteed.
Although complete participants have the advantage of understanding the history, rituals, and jargon of the organization, their pre-existing biases may greatly cloud their interpretation of events.
Both types of observers must pay considerable attention to the concept of trust—complete observers, if the participants are aware of his or her presence, may have difficulty gaining the trust of the group and getting them to behave as they naturally would (consider the Hawthorne effect that states that people behave artificially when they know that they are being observed). Complete participants may begin with the trust of the participants, but will likely find themselves navigating a difficult path, particularly if they become aware of behaviors and activities that portray some members of the group in a negative light.

So what is the difference between an observer-as-participant and a participant-as-observer? A few years ago, a colleague was doing an ethnographic study of the emergency room in a large hospital. She had no training in the medical profession. She received permission to conduct observations and interviews over the course of several months. She began the study as a complete observer. However, over the course of her ethnographic study, she had multiple experiences that caused her to shift from complete observer to an observer-as-participant role. On one occasion, due to shortages on the staff, she was asked to hold a patient’s leg in place in order for the doctor to attempt to set the broken leg prior to putting it in a cast. Needless to say, the colleague was not expecting to play any kind of active role in the hospital emergency room other than active observation. So, an observer as participant is when an individual maintains the primary role of observation, but on occasion is asked to participate. Another example is when other professors visit your classroom in order to observe and evaluate your professor or teaching assistant. In this case the primary role is the observation, but in some circumstances the observers find themselves participating in class activities such as discussion or role-playing. Now imagine that you are a nurse in an emergency room who has been asked by administration to document communication patterns in the emergency room and recommend improvements. The participant-as-observer still has the primary responsibility of being a nurse in the emergency room, but he or she might also have specific time in meetings or every hour or so to document and reflect on observations. In this way she/he fulfills the primary role of nurse, but also is able to allocate time to observation and analysis on the side.

It is important to determine which observation role is best suited for your research. You must consider whether you are an insider or an outsider for the organization. You must then determine if you will be taking a covert (undercover) role or a more overt (out in the open) role. Regardless of the type of observation in which the researcher engages, specific and systematic expectations for data gathering and analysis govern your research. The role that you take impacts the type of data that you are able to collect.

Research Questions, Seldom Hypotheses

Qualitative research proceeds inductively—beginning with a specific group or a specific question and then gathering data in order to lead to a general explanation or perhaps even a theory. Qualitative researchers are seldom engaged in testing existing theory in the same sense that quantitative researchers are. Therefore, qualitative research relies on broad research questions asking “how” or “what” rather than testable hypotheses that make clear predictions. Consider the following sample research questions from three different qualitative studies.

RQ1: In what ways are employees’ constructions of mistreatment in the workplace muted or privileged? RQ2: What are the processes that silence or encourage discussion of mistreatment by employees? (Meares, Oetzel, Torres, Derkacs, & Ginossar, 2004, p. 9)

RQ1: What are the components of high self-esteem for the women in the study? RQ2: How do they say they manage the construction and maintenance of high self-esteem in their lives? (DeFrancisco & Chatham-Carpenter, 2000, p. 77)

RQ1: How do disabled organizational members experience and negotiate organizational assimilation? (Cohen & Avanzino, 2010, p. 278)

While these three qualitative studies clearly follow the pattern of asking “how” or “what” questions, it is important to remember that, in general, there is more flexibility regarding the normative presentation of qualitative research. In some cases, such as the research of Wong and Goodwin (2009), because there was already an existing body of evidence on which to base their research, they proffered hypotheses with their qualitative study on marital satisfaction. Their hypotheses included:

H1: Bonding and the interactions between the spouses would be more important in individuals’ evaluation of marital relationships in modernized societies where independence is valued. H2: Relationships with other family members would be more important in the evaluation of marital relationships in societies where interdependence is valued. H3: Financial security would be a more important factor in marital satisfaction in less modernized settings. (Wong & Goodwin, 2009, p. 1014)

Wong and Goodwin gathered their data through in-depth qualitative interviews, but due to the large body of existing scholarship on marital satisfaction, they were confident in presenting hypotheses. However, it is necessary to point out that while hypotheses in qualitative research may exist, they are rare.

To further demonstrate the variation in qualitative research, some research studies may eschew research questions altogether. In these cases there is often a research purpose stated prior to describing the methods, but this purpose may take the form of a tentative statement rather than a research question. For example, Weinstein (2007) used field observations, interviews, and written documents to explore how inner city youths used writing (poetry, lyrics, etc.) to negotiate gender and sexual identity. She states, “I hope to contribute to the ongoing work done by researchers on adolescents’ and young adults’ uses of written and oral composition to find workable identities in the midst of multiple and shifting social contexts” (Weinstein, 2007, p. 30). In another case, Hundley and Shyles (2010) studied teenagers’ perceptions of technology and, rather than asking a research question, they simply stated, “this research continues the line of inquiry by listening to teenagers and gaining a perspective on what they think about emerging digital technologies and the functions various devices serve in their lives” (p. 418).

Thus, variation exists regarding the presentation of research goals in qualitative research. Goals may range from general purpose statements to specific research questions. Although hypotheses are rare, and research questions and research statements are more typical in qualitative research, one must remember that regardless of the approach, the methodology must be in the service of the overall research purpose.

Types of Data in Qualitative Research

The data for qualitative research takes many forms. Interviews and focus groups provide responses to carefully designed questions. Observation and ethnography provide detailed notes of the research setting. Participant responses or observation events may range from brief, specific responses to detailed, descriptive stories. A truly extensive ethnography, for example, might combine detailed field notes, descriptive stories, and specific responses to field interview questions. Stories, field notes, and interview/focus group responses are all valid forms of qualitative research data.

Stories. Some qualitative techniques, such as narrative analysis, seek to elicit stories from the research participants, while in other cases, like interviews or focus groups, stories may arise naturally over the course of the research. Fisher (1984) said that it is natural for humans to communicate using stories. It is not hard to imagine the range of situations in which stories may either be elicited or arise spontaneously. Imagine an interview question where the researcher asks, “tell me about a time when you experienced conflict with a co-worker?” Or, consider doing research on U.S. wedding rehearsal dinner rituals. One can imagine the richness of the stories naturally arising in that setting. Qualitative research offers details and descriptions that are richer and more in-depth than quantitative research—the collecting of stories is a perfect way to capture the richness of our social activity.

Field notes . Whether one is observing a focus group, an emergency room, or the proceedings of a student organization meeting, field notes are a necessary tool for capturing the social activity as it unfolds. If the researcher is conducting an ethnography, and is involved in the act of cultural immersion, the observational field notes provide the data for the study. Field notes are a record of the activities of the participants of a study. The field notes are a written log of the researcher’s observations. Perhaps you like to go to the mall and watch the people as they come and go. Even with a good memory it is doubtful that you would be able to remember more than one or two interesting points if asked about it the next day. It is for this reason that detailed field notes, which describe the setting and participants in real time, are the best way of documenting a researcher’s time in the social environment.

For an ethnographer, the field notes are the data that allow the researcher to develop a credible argument in the final report. For a researcher observing a focus group, field notes enable the researcher to note the physical setting of the focus group or to chart how interaction proceeds over the course of the focus group. One of the most common ways to set up your field notes is to divide your page from top to bottom down the middle. On the left side of the page, the researcher should include specific observations, while on the right side of the page, the researcher should include tentative questions or concepts or future ideas. It is always important to also include the date, time, and location of the observation—and perhaps even a map of the research setting.

A good student activity is to select a location—the union, a class, a restaurant, etc.—and practice taking your own field notes. Just spend 30 minutes observing the location and see how accurately you are able to capture the setting and the ongoing interaction among the participants.

Consider the following example of field notes from observation of a graduate class:

In-depth interviews & focus groups. Quite a bit of qualitative data is neither collected using field notes nor involves a detailed story. Much of the data follows the natural give and take of everyday conversation. Whenever possible, an audio recorder is a useful tool for capturing participant responses to interview questions. Open-ended responses that are not as extensive as a detailed story are very common in qualitative data. If brief, closed-ended responses are the type of data you need, you probably want to consider a quantitative survey. However, if you are interested in understanding how and why participants engage in certain activities or adopt certain values, qualitative interviewing will likely provide you with the type of data you need.

Stories, field notes, interview and focus group responses, and field notes are three common forms of data in qualitative research. All researchers are interested in producing the most accurate and valid conclusions from their data. Prior to and during the research process, there are choices the researcher can make to strengthen his or her results. The choices are rooted in a process called triangulation , which means you may choose multiple ways to collect data or multiple methods to explore the answer to your research question/s (Denzin, 2006).

Sampling Characteristics

Selecting the participants for a qualitative study often relies on a very deliberate process. Whereas quantitative research improves its accuracy through random sampling that is representative of the population to which it seeks to extend its results, qualitative research, with its emphasis on context and focus on understanding, will generally use a purposive non-random sampling strategy, rather than a random, sampling process. Once again, the fact that qualitative research proceeds inductively (starting with a specific group or setting), rather than deductively, reinforces the necessity of purposive sampling practices. If a researcher wants to observe and understand the communication practices at a large retail store, he or she would purposely select a retail store as the setting for the study. According to Schwandt (2001), qualitative samples “are chosen not for their representativeness but for their relevance to the research question, analytical framework, and explanation or account being developed in the research” (p. 232).

Another characteristic of qualitative research samples concerns sample size. Because qualitative research focuses on understanding rather than generalizations, the size of the sample is typically much smaller than a sample for a quantitative survey. For example, consider the amount of time it takes to set up, conduct, and transcribe ten average length interviews compared to an on-line survey that automatically compiles the data and uploads it into a statistical program. Also, if a researcher wants to study the large retail store with many departments, it is easy to imagine the amount of time necessary to complete a thorough ethnography. Even if the researcher only chooses to focus on a single department within a retail store, observing different shifts and different workers would take a considerable investment of time. Qualitative samples are both purposefully selected, to meet the research objective, and deliberately small, to be manageable for the researcher.

The Importance of Triangulation

All researchers seek to produce an accurate or credible account of the phenomenon under investigation. Researchers have a variety of options to improve the credibility of their studies. Triangulation is the process of using two or more types of evidence to provide a more clear and accurate interpretation of the data. Triangulation takes multiple forms from researcher triangulation to data triangulation. The basic premise behind triangulation is that if the multiple data sources converge, validity/credibility has been enhanced. We will briefly discuss several of the more popular forms of triangulation.

Multiple methodologies . This type of triangulation involves the researcher or researchers using multiple techniques to gather the data. Suppose that a researcher wants to study the communication practices of a local restaurant. One of the ways that the researcher might collect data is by interviewing the employees of the restaurant. The results of the interviews might paint a very accurate picture of restaurant activities. However, the researcher might also want to observe the restaurant as the social actors engage in their day-to-day activities. The idea behind triangulation is that the data collected from the interviews and the data collected from the observations of the restaurant, when combined, paint a more complete and accurate picture of the restaurant than either one of the methods alone. Of course, a researcher could also include a third method, focus groups, in an effort to corroborate the conclusions drawn from the interviews and the observations. Using multiple methodologies for triangulation does not have to be limited to qualitative methods. For example, it is very common for a researcher to conduct interviews in order to gain a basic understanding of a concept and then use that information to create quantitative surveys to distribute to a larger sample. The goal is to create the most credible interpretation of the data, and triangulation of methods is one way to improve the accuracy of a study.

Multiple researchers . This type of triangulation involves multiple researchers gathering data on the same subject. In the example regarding the ethnographic study of a retail establishment, it is easy to see how a research team would have an easier time collecting observations than an individual researcher would. It is not just that multiple researchers can spread out and cover more ground, thereby creating a more fully realized picture of the organization, but also that multiple researchers increase the chance of accurately capturing all of the activities occurring when viewing the same event. Think of all of the activities going on during a typical organizational meeting—multiple researchers would be able to capture a fuller spectrum of social activity in less time than just one researcher. Additionally, multiple researchers contribute to the development of intersubjective understanding. Multiple researchers can mitigate some of the biases of each researcher, helping to avoid reaching a premature conclusion or being overly subjective.

There are other forms of triangulation, such as multiple research settings (observing at different times or in different places) or multiple disciplinary approaches (one observer versed in organizational communication and another versed in organizational behavior). These forms of triangulation are not mutually exclusive; researchers can combine, and often do combine, a variety of these approaches.

General Strengths and Weaknesses of Qualitative Research

Perhaps the greatest strength of qualitative research is the sheer amount of depth it can bring to our understanding of social action. Qualitative data can capture many of the complexities of human interaction that are unable to be uncovered through a quantitative survey. Because it proceeds inductively, it is both strong at discovering new phenomena and at generating theories of human behavior. Qualitative data collection often occurs in the participants’ natural environment, improving the ecological validity of the study. As long as the researchers are able to overcome the Hawthorne effect, the data collected should reflect actual behaviors in ways that self-reported surveys or laboratory studies are unable to reflect. Finally, qualitative researchers allow the participants to tell their own stories rather than reducing the stories to numbers.

Qualitative research also has obvious weaknesses because the researcher is the data collection instrument, so the quality of the data is only as good as the researcher. Has the researcher collected enough data to paint an accurate picture? Has the researcher attempted to minimize individual bias to the fullest extent? These concerns represent just a few of the problems that could result from the subjective nature of qualitative research. Qualitative research is not good for generalizing results to a larger population and it is not good for examining causal relationships. There is also a considerable investment of time associated with this type of research.

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Introduction to Research Methods A Hands-on Approach

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“ Introduction to Research Methods is an excellent resource for students and instructors alike. With readable text in an approachable tone, it effectively covers the breadth of topics related to research methods. Its lucidity is stellar.”

“ Introduction to Research Methods: A Hands-on Approach is highly relevant to the work my undergraduate students do and is delivered at a level they can follow. It does a great job of presenting complex information in an easy-to-understand format. At the graduate level, I could see this text serving as a primary read but then supplementing with more complex articles/chapters. Accessibility of the content is a core strength of this text. It makes in-depth content easy to follow for the novice researcher, while at the same time is engaging enough to not be bland for those with research experience. Overall, this text reads as a road map for how to conduct ethical research and provides the necessary step-by-step instructions on how to be successful during the research process.”

“ Introduction to Research Methods: A Hands-on Approach is an excellent text that presents research methods in an easy-to-understand way with examples that foster critical thinking."

“The hands-on, practical approach to Pajo’s Introduction to Research Methods is a huge key strength.”

Very useful for research methods

The new edition is available in SAGE Vantage , an intuitive learning platform that integrates quality SAGE textbook content with assignable multimedia activities and auto-graded assessments to drive student engagement and ensure accountability. Unparalleled in its ease of use and built for dynamic teaching and learning, Vantage offers customizable LMS integration and best-in-class support. Learn more.
A new chapter on Big Data offers a window into the possibilities of what social scientists are accomplishing in the world of machine learning and the endless possibilities of data visualization. It familiarizes students with current and future opportunities in social and behavioral science.
A completely revised chapter on qualitative designs and data collection illustrates how qualitative designs fit within scientific research methods by emphasizing similarities and identifying differences.
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A conversational and jargon-free writing style brings the relevance of research to life.
Research in Action features illustrate real, annotated research examples, giving students the skills to read and interpret research they may encounter in their everyday lives.
Research Workshop features offer step-by-step help on practical topics that extend beyond the chapter to provide hands-on tips for students conducting their own research.
Ethical Considerations within each chapter address different aspects of research to emphasize ethics as an integral part of the research conversation.
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Chapter 5: The Literature Review

Learning Objectives

Describe a literature review and explain its purpose.
Describe the steps in undertaking a literature review.
Write a literature review.
Identify acceptable sources to include in your literature review.
Apply the five ‘C’s of writing a literature review.
Compare a literature review, an essay and an annotated bibliography.
Explain the importance of APA referencing and list some of the sources for getting assistance with APA referencing.

In this chapter, we will focus on writing a literature review. As part of this focus we will concentrate on four key aspects, as follows:

The purpose behind a literature review and where it fits in the research process;
The difference between a literature review, an essay, and an annotated bibliography;
The special aspects that distinguish a literature review from other styles of academic writing; and
The way to conduct a literature review and is the importance of reviewing previous research studies.

If you have never written a literature review, and even if you have, this chapter will provide valuable information for you. Understanding how to write a literature review is important because it is quite likely that you will have to do another one at some point in your academic and/or professional career.

Research Methods, Data Collection and Ethics Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Chapter 5: Experimental Research

In the late 1960s social psychologists John Darley and Bibb Latané proposed a counter-intuitive hypothesis. The more witnesses there are to an accident or a crime, the less likely any of them is to help the person who is experiencing the crime (Darley & Latané, 1968) [1] .

They also suggested the theory that this phenomenon occurs because each witness feels less responsible for helping—a process referred to as the “diffusion of responsibility.” Darley and Latané noted that their ideas were consistent with many real-world cases. For example, a New York woman named Catherine “Kitty” Genovese was assaulted and murdered while several witnesses evidently failed to help. But Darley and Latané also understood that such isolated cases did not provide convincing evidence for their hypothesized “bystander effect.” There was no way to know, for example, whether any of the witnesses to Kitty Genovese’s murder would have helped had there been fewer of them.

So to test their hypothesis, Darley and Latané created a simulated emergency situation in a laboratory. Each of their university student participants was isolated in a small room and told that they would be having a discussion about university life with other students via an intercom system. Early in the discussion, however, one of the students began having what seemed to be an epileptic seizure. Over the intercom came the following: “I could really-er-use some help so if somebody would-er-give me a little h-help-uh-er-er-er-er-er c-could somebody-er-er-help-er-uh-uh-uh (choking sounds)…I’m gonna die-er-er-I’m…gonna die-er-help-er-er-seizure-er- [chokes, then quiet]” (Darley & Latané, 1968, p. 379) .

In actuality, there were no other students. These comments had been prerecorded and were played back to create the appearance of a real emergency. The key to the study was that some participants were told that the discussion involved only one other student (the person experiencing this event), others were told that it involved two other students, and still others were told that it included five other students. Because this was the only difference between these three groups of participants, any difference in their tendency to help the person experiencing the event would have to have been caused by it. And sure enough, the likelihood that the participant left the room to seek help for the “person impacted by this event” decreased from 85% to 62% to 31% as the number of “witnesses” increased.

The Parable of the 38 Witnesses

The story of Kitty Genovese has been told and retold in numerous psychology textbooks. The standard version is that there were 38 witnesses to the crime, that all of them watched (or listened) for an extended period of time, and that none of them did anything to help. However, recent scholarship suggests that the standard story is inaccurate in many ways (Manning, Levine, & Collins, 2007) [2] . For example, only six eyewitnesses testified at the trial, none of them was aware that they were witnessing a lethal assault, and there have been several reports of witnesses calling the police or even coming to the aid of Kitty Genovese. Although the standard story inspired a long line of research on the bystander effect and the diffusion of responsibility, it may also have directed researchers’ and students’ attention away from other equally interesting and important issues in the psychology of helping—including the conditions in which people do in fact respond collectively to emergency situations.

The research that Darley and Latané conducted was a particular kind of study called an experiment. Experiments are used to determine not only whether there is a meaningful relationship between two variables but also whether the relationship is a causal one that is supported by statistical analysis. For this reason, experiments are one of the most common and useful tools in the psychological researcher’s toolbox. In this chapter, we look at experiments in detail. We will first consider what sets experiments apart from other kinds of studies and why they support causal conclusions while other kinds of studies do not. We then look at two basic ways of designing an experiment—between-subjects designs and within-subjects designs—and discuss their pros and cons. Finally, we consider several important practical issues that arise when conducting experiments.

Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility. Journal of Personality and Social Psychology, 4 , 377–383. ↵
Manning, R., Levine, M., & Collins, A. (2007). The Kitty Genovese murder and the social psychology of helping: The parable of the 38 witnesses. American Psychologist, 62 , 555–562. ↵

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1.5: Chapter 5 Research Design

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Key Attributes of a Research Design

The quality of research designs can be defined in terms of four key design attributes: internal validity, external validity, construct validity, and statistical conclusion validity.

Writing The Methodology Chapter

5 Time-Saving Tips & Tools

By: David Phair (PhD) and Amy Murdock (PhD) | July 2022

The methodology chapter is a crucial part of your dissertation or thesis – it’s where you provide context and justification for your study’s design. This in turn demonstrates your understanding of research theory, which is what earns you marks .

Over the years, we’ve helped thousands of students navigate this tricky section of the research process. In this post, we’ll share 5 time-saving tips to help you effectively write up your research methodology chapter .

Overview: Writing The Methodology Chapter

Develop a (rough) outline before you start writing
Draw inspiration from similar studies in your topic area
Justify every research design choice that you make
Err on the side of too much detail , rather than too little
Back up every design choice by referencing literature

1. Develop an outline before you start writing

The first thing to keep in mind when writing your methodology chapter (and the rest of your dissertation) is that it’s always a good idea to sketch out a rough outline of what you are going to write about before you start writing . This will ensure that you stay focused and have a clear structural logic – thereby making the writing process simpler and faster.

An easy method of finding a structure for this chapter is to use frameworks that already exist, such as Saunder’s “ research onion ” as an example. Alternatively, there are many free methodology chapter templates for you to use as a starting point, so don’t feel like you have to create a new one from scratch.

Next, you’ll want to consider what your research approach is , and how you can break it down from a top-down angle, i.e., from the philosophical down to the concrete/tactical level. For example, you’ll need to articulate the following:

Are you using a positivist , interpretivist , or pragmatist approach ?
Are you using inductive or deductive reasoning?
Are you using a qualitative , quantitative, or mixed methods study?

Keep these questions front of mind to ensure that you have a clear, well-aligned line of argument that will maintain your chapter’s internal and external consistency.

Remember, it’s okay if you feel overwhelmed when you first start the methodology chapter. Nobody is born with an innate knowledge of how to do this, so be prepared for the learning curve associated with new research projects. It’s no small task to write up a dissertation or thesis, so be kind to yourself!

Starting the process with a chapter outline will help keep your writing focused and ensure that the chapter has a clear structural logic.

2. Take inspiration from other studies

Generally, there are plenty of existing journal articles that will share similar methodological approaches to your study. With any luck, there will also be existing dissertations and theses that adopt a similar methodological approach and topic. So, consider taking inspiration from these studies to help curate the contents of your methodology chapter.

Students often find it difficult to choose what content to include in the methodology chapter and what to leave for the appendix. By reviewing other studies with similar approaches, you will get a clearer sense of your discipline’s norms and characteristics . This will help you, especially in terms of deciding on the structure and depth of discussion.

While you can draw inspiration from other studies, remember that it’s vital to pay close attention to your university’s specific guidelines, so you can anticipate departmental expectations of this section’s layout and content (and make it easier to work with your supervisor). Doing this is also a great way to figure out how in-depth your discussion should be. For example, word-count guidelines can help you decide whether to include or omit certain information.

Need a helping hand?

3. Justify every design choice you make

The golden rule of the methodology chapter is that you need to justify each and every design choice that you make, no matter how small or inconsequential it may seem. We often see that students merely state what they did instead of why they did what they did – and this costs them marks.

Keep in mind that you need to illustrate the strength of your study’s methodological foundation. By discussing the “what”, “why” and “how” of your choices, you demonstrate your understanding of research design and simultaneously justify the relevancy and efficacy of your methodology – both of which will earn you marks.

It’s never an easy task to conduct research. So, it’s seldom the case that you’ll be able to use the very best possible methodology for your research (e.g. due to time or budgetary constraints ). That’s okay – but make sure that you explain and justify your use of an alternate methodology to help justify your approach.

Ultimately, if you don’t justify and explain the logic behind each of your choices, your marker will have to assume that you simply didn’t know any better . So, make sure that you justify every choice, especially when it is a subpar choice (due to a practical constraint, for example). You can see an example of how this is done here.

The golden rule of the methodology chapter is that you need to justify each and every design choice that you make, no matter how small.

4. Err on the side of too much detail

We often see a tendency in students to mistakenly give more of an overview of their methodology instead of a step-by-step breakdown . Since the methodology chapter needs to be detailed enough for another researcher to replicate your study, your chapter should be particularly granular in terms of detail.

Whether you’re doing a qualitative or quantitative study, it’s crucial to convey rigor in your research. You can do this by being especially detailed when you discuss your data, so be absolutely clear about your:

Sampling strategy
Data collection method(s)
Data preparation
Analysis technique(s)

As you will likely face an extensive period of editing at your supervisor/reviewer’s direction, you’ll make it much easier for yourself if you have more information than you’d need. Some supervisors expect extensive detail around a certain aspect of your dissertation (like your research philosophy), while others may not expect it at all.

Remember, it’s quicker and easier to remove/ trim down information than it is to add information after the fact, so take the time to show your supervisor that you know what you’re talking about (methodologically) and you’re doing your best to be rigorous in your research.

The methodology chapter needs to be detailed enough information for another researcher to replicate your study, so don't be shy on detail.

5. Provide citations to support each design choice

Related to the issue of poor justification (tip #3), it’s important include high-quality academic citations to support the justification of your design choices. In other words, it’s not enough to simply explain why you chose a specific approach – you need to support each justification with reference to academic material.

Simply put, you should avoid thinking of your methodology chapter as a citation-less section in your dissertation. As with your literature review, your methods section must include citations for every decision you make, since you are building on prior research. You must show that you are making decisions based on methods that are proven to be effective, and not just because you “feel” that they are effective.

When considering the source of your citations, you should stick to peer-reviewed academic papers and journals and avoid using websites or blog posts (like us, hehe). Doing this will demonstrate that you are familiar with the literature and that you are factoring in what credible academics have to say about your methodology.

As a final tip, it’s always a good idea to cite as you go . If you leave this for the end, then you’ll end up spending a lot of precious time retracing your steps to find your citations and risk losing track of them entirely. So, be proactive and drop in those citations as you write up . You’ll thank yourself later!

Let’s Recap…

In this post, we covered 5 time-saving tips for writing up the methodology chapter:

Look at similar studies in your topic area
Justify every design choice that you make
Back up every design choice by referencing methodology literature

If you’ve got any questions relating to the methodology chapter, feel free to drop a comment below. Alternatively, if you’re interested in getting 1-on-1 help with your thesis or dissertation, be sure to check out our private coaching service .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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Research on the Development and Price Prediction Method of Space Products Based on Cost Analysis

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First Online: 11 May 2024
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Jie Ren 40

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1188))

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International Conference On Signal And Information Processing, Networking And Computers

The technology of products in the space industry is advancing in rapid pace, resulting in prices variation. The purpose of space product price prediction is to make scientific estimations and speculations on the trend of space product prices based on specific methodology, survey, and mathematical analysis, with a focus on the available statistical data and relevant information to unveil the correlations that underlay procurement activities. Efforts have been made in prediction methodologies taxonomy, qualitative and quantitative prediction, methodology development, data modelling establishment and correction, which provide concrete theoretical support for the development of aerospace products and price prediction.

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Xia, F.: Research on the prediction method of technology integration direction of emerging industries. Harbin University of Technology, Harbin (2020)

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Liu, S., Dang, Y.: Forecasting Methods and Techniques. Higher Education Press, Beijing (2005)

Wang, K.: The foundation of probability science - An investigation of the dispute between subjectivist and objectivist views of probability. Donghua University, Shanghai (2020)

Han, X., Yu, Y., Wang, L.: Key role of government chief data officer in digital transformation: findings from the delphi method. Digital Lib. Forum 19 (3) (2023)

Li, X., Gu, M.: Digital formalism in the digital transformation of the public sector: an actor-based analytical framework and typological analysis. E-Government (2022)

Hu, A., Li, C.: Expectile regression analysis based on distributed big data. Math. Appl. 35 (4) (2022)

Xiao, G., Wang, R.: Code for linear regression analysis. J. Yangzhou Polytechn. College 24 (2) (2020)

Zhang, J., Yu, J.: Parameter resolution of estimation methods for linear regression models. Acta Math. Sci. 40 (5) (2020)

Hu, X.Y., Zhang, Z.: Empirical likelihood inference of error variance in logistic regression models with fixed design case. J. Guangxi Univ. Nat. (Natl. Sci. Edn.) 27 (3) (2021)

Cui, L., Wu, D., Cheng, L.: Robust estimation and outlier detection based on stepwise regression. J. Shenyang Normal Univ. (Natl. Sci. Edn.) 38 (6) (2018)

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Ren, J. (2024). Research on the Development and Price Prediction Method of Space Products Based on Cost Analysis. In: Wang, Y., Zou, J., Xu, L., Ling, Z., Cheng, X. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2023. Lecture Notes in Electrical Engineering, vol 1188. Springer, Singapore. https://doi.org/10.1007/978-981-97-2124-5_25

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Table of Contents

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Chapter 5. Sampling

The “Who” of Your Research Study

Sampling People

When Your Population is Not Composed of People

Case Studies

Content: Documents, Narrative Accounts, And So On

Goals of Qualitative Sampling versus Goals of Quantitative Sampling

What is the Correct “Number” to Sample?

Examples of “Sample” Sections in Journal Articles

Final Words

Further Readings

Chapter 5 Research Design

Key Attributes of a Research Design

Improving Internal and External Validity

Popular Research Designs

Selecting Research Designs

The Qualitative Worldview

Assumptions of Qualitative Research

The Traditions of Qualitative Research

Hermeneutics

Phenomenology

Symbolic Interactionism

Attributes of Qualitative Research

Observation

Research Questions, Seldom Hypotheses

Types of Data in Qualitative Research

Sampling Characteristics

The Importance of Triangulation

General Strengths and Weaknesses of Qualitative Research

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'Research Methods' Practice Quiz Chapter 5

1.5: Chapter 5 Research Design

Key Attributes of a Research Design

Writing The Methodology Chapter

Overview: Writing The Methodology Chapter

1. Develop an outline before you start writing

2. Take inspiration from other studies

Need a helping hand?

3. Justify every design choice you make

4. Err on the side of too much detail

5. Provide citations to support each design choice

Let’s Recap…

Psst... there’s more!

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