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• Descriptive Research | Definition, Types, Methods & Examples

Descriptive Research | Definition, Types, Methods & Examples

Published on May 15, 2019 by Shona McCombes . Revised on June 22, 2023.

Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what , where , when and how   questions , but not why questions.

A descriptive research design can use a wide variety of research methods  to investigate one or more variables . Unlike in experimental research , the researcher does not control or manipulate any of the variables, but only observes and measures them.

Table of contents

When to use a descriptive research design, descriptive research methods, other interesting articles.

Descriptive research is an appropriate choice when the research aim is to identify characteristics, frequencies, trends, and categories.

It is useful when not much is known yet about the topic or problem. Before you can research why something happens, you need to understand how, when and where it happens.

Descriptive research question examples

• How has the Amsterdam housing market changed over the past 20 years?
• Do customers of company X prefer product X or product Y?
• What are the main genetic, behavioural and morphological differences between European wildcats and domestic cats?
• What are the most popular online news sources among under-18s?
• How prevalent is disease A in population B?

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Descriptive research is usually defined as a type of quantitative research , though qualitative research can also be used for descriptive purposes. The research design should be carefully developed to ensure that the results are valid and reliable .

Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages and patterns. Common uses of surveys include:

• Describing the demographics of a country or region
• Gauging public opinion on political and social topics
• Evaluating satisfaction with a company’s products or an organization’s services

Observations

Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. This method is often used by psychological, social and market researchers to understand how people act in real-life situations.

Observation of physical entities and phenomena is also an important part of research in the natural sciences. Before you can develop testable hypotheses , models or theories, it’s necessary to observe and systematically describe the subject under investigation.

Case studies

A case study can be used to describe the characteristics of a specific subject (such as a person, group, event or organization). Instead of gathering a large volume of data to identify patterns across time or location, case studies gather detailed data to identify the characteristics of a narrowly defined subject.

Rather than aiming to describe generalizable facts, case studies often focus on unusual or interesting cases that challenge assumptions, add complexity, or reveal something new about a research problem .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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What is Descriptive Research? Definition, Methods, Types and Examples

Descriptive research is a methodological approach that seeks to depict the characteristics of a phenomenon or subject under investigation. In scientific inquiry, it serves as a foundational tool for researchers aiming to observe, record, and analyze the intricate details of a particular topic. This method provides a rich and detailed account that aids in understanding, categorizing, and interpreting the subject matter.

Descriptive research design is widely employed across diverse fields, and its primary objective is to systematically observe and document all variables and conditions influencing the phenomenon.

After this descriptive research definition, let’s look at this example. Consider a researcher working on climate change adaptation, who wants to understand water management trends in an arid village in a specific study area. She must conduct a demographic survey of the region, gather population data, and then conduct descriptive research on this demographic segment. The study will then uncover details on “what are the water management practices and trends in village X.” Note, however, that it will not cover any investigative information about “why” the patterns exist.

Table of Contents

What is descriptive research?

If you’ve been wondering “What is descriptive research,” we’ve got you covered in this post! In a nutshell, descriptive research is an exploratory research method that helps a researcher describe a population, circumstance, or phenomenon. It can help answer what , where , when and how questions, but not why questions. In other words, it does not involve changing the study variables and does not seek to establish cause-and-effect relationships.

Importance of descriptive research

Now, let’s delve into the importance of descriptive research. This research method acts as the cornerstone for various academic and applied disciplines. Its primary significance lies in its ability to provide a comprehensive overview of a phenomenon, enabling researchers to gain a nuanced understanding of the variables at play. This method aids in forming hypotheses, generating insights, and laying the groundwork for further in-depth investigations. The following points further illustrate its importance:

Provides insights into a population or phenomenon: Descriptive research furnishes a comprehensive overview of the characteristics and behaviors of a specific population or phenomenon, thereby guiding and shaping the research project.

Offers baseline data: The data acquired through this type of research acts as a reference for subsequent investigations, laying the groundwork for further studies.

Allows validation of sampling methods: Descriptive research validates sampling methods, aiding in the selection of the most effective approach for the study.

Helps reduce time and costs: It is cost-effective and time-efficient, making this an economical means of gathering information about a specific population or phenomenon.

Ensures replicability: Descriptive research is easily replicable, ensuring a reliable way to collect and compare information from various sources.

When to use descriptive research design?

Determining when to use descriptive research depends on the nature of the research question. Before diving into the reasons behind an occurrence, understanding the how, when, and where aspects is essential. Descriptive research design is a suitable option when the research objective is to discern characteristics, frequencies, trends, and categories without manipulating variables. It is therefore often employed in the initial stages of a study before progressing to more complex research designs. To put it in another way, descriptive research precedes the hypotheses of explanatory research. It is particularly valuable when there is limited existing knowledge about the subject.

Some examples are as follows, highlighting that these questions would arise before a clear outline of the research plan is established:

• In the last two decades, what changes have occurred in patterns of urban gardening in Mumbai?
• What are the differences in climate change perceptions of farmers in coastal versus inland villages in the Philippines?

Characteristics of descriptive research

Coming to the characteristics of descriptive research, this approach is characterized by its focus on observing and documenting the features of a subject. Specific characteristics are as below.

• Quantitative nature: Some descriptive research types involve quantitative research methods to gather quantifiable information for statistical analysis of the population sample.
• Qualitative nature: Some descriptive research examples include those using the qualitative research method to describe or explain the research problem.
• Observational nature: This approach is non-invasive and observational because the study variables remain untouched. Researchers merely observe and report, without introducing interventions that could impact the subject(s).
• Cross-sectional nature: In descriptive research, different sections belonging to the same group are studied, providing a “snapshot” of sorts.
• Springboard for further research: The data collected are further studied and analyzed using different research techniques. This approach helps guide the suitable research methods to be employed.

Types of descriptive research

There are various descriptive research types, each suited to different research objectives. Take a look at the different types below.

• Surveys: This involves collecting data through questionnaires or interviews to gather qualitative and quantitative data.
• Observational studies: This involves observing and collecting data on a particular population or phenomenon without influencing the study variables or manipulating the conditions. These may be further divided into cohort studies, case studies, and cross-sectional studies:
• Cohort studies: Also known as longitudinal studies, these studies involve the collection of data over an extended period, allowing researchers to track changes and trends.
• Case studies: These deal with a single individual, group, or event, which might be rare or unusual.
• Cross-sectional studies : A researcher collects data at a single point in time, in order to obtain a snapshot of a specific moment.
• Focus groups: In this approach, a small group of people are brought together to discuss a topic. The researcher moderates and records the group discussion. This can also be considered a “participatory” observational method.
• Descriptive classification: Relevant to the biological sciences, this type of approach may be used to classify living organisms.

Descriptive research methods

Several descriptive research methods can be employed, and these are more or less similar to the types of approaches mentioned above.

• Surveys: This method involves the collection of data through questionnaires or interviews. Surveys may be done online or offline, and the target subjects might be hyper-local, regional, or global.
• Observational studies: These entail the direct observation of subjects in their natural environment. These include case studies, dealing with a single case or individual, as well as cross-sectional and longitudinal studies, for a glimpse into a population or changes in trends over time, respectively. Participatory observational studies such as focus group discussions may also fall under this method.

Researchers must carefully consider descriptive research methods, types, and examples to harness their full potential in contributing to scientific knowledge.

Examples of descriptive research

Now, let’s consider some descriptive research examples.

• In social sciences, an example could be a study analyzing the demographics of a specific community to understand its socio-economic characteristics.
• In business, a market research survey aiming to describe consumer preferences would be a descriptive study.
• In ecology, a researcher might undertake a survey of all the types of monocots naturally occurring in a region and classify them up to species level.

These examples showcase the versatility of descriptive research across diverse fields.

Advantages of descriptive research

There are several advantages to this approach, which every researcher must be aware of. These are as follows:

• Owing to the numerous descriptive research methods and types, primary data can be obtained in diverse ways and be used for developing a research hypothesis .
• It is a versatile research method and allows flexibility.
• Detailed and comprehensive information can be obtained because the data collected can be qualitative or quantitative.
• It is carried out in the natural environment, which greatly minimizes certain types of bias and ethical concerns.
• It is an inexpensive and efficient approach, even with large sample sizes

Disadvantages of descriptive research

On the other hand, this design has some drawbacks as well:

• It is limited in its scope as it does not determine cause-and-effect relationships.
• The approach does not generate new information and simply depends on existing data.
• Study variables are not manipulated or controlled, and this limits the conclusions to be drawn.
• Descriptive research findings may not be generalizable to other populations.
• Finally, it offers a preliminary understanding rather than an in-depth understanding.

To reiterate, the advantages of descriptive research lie in its ability to provide a comprehensive overview, aid hypothesis generation, and serve as a preliminary step in the research process. However, its limitations include a potential lack of depth, inability to establish cause-and-effect relationships, and susceptibility to bias.

Frequently asked questions

When should researchers conduct descriptive research.

Descriptive research is most appropriate when researchers aim to portray and understand the characteristics of a phenomenon without manipulating variables. It is particularly valuable in the early stages of a study.

What is the difference between descriptive and exploratory research?

Descriptive research focuses on providing a detailed depiction of a phenomenon, while exploratory research aims to explore and generate insights into an issue where little is known.

What is the difference between descriptive and experimental research?

Descriptive research observes and documents without manipulating variables, whereas experimental research involves intentional interventions to establish cause-and-effect relationships.

Is descriptive research only for social sciences?

No, various descriptive research types may be applicable to all fields of study, including social science, humanities, physical science, and biological science.

How important is descriptive research?

The importance of descriptive research lies in its ability to provide a glimpse of the current state of a phenomenon, offering valuable insights and establishing a basic understanding. Further, the advantages of descriptive research include its capacity to offer a straightforward depiction of a situation or phenomenon, facilitate the identification of patterns or trends, and serve as a useful starting point for more in-depth investigations. Additionally, descriptive research can contribute to the development of hypotheses and guide the formulation of research questions for subsequent studies.

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Characteristics of Qualitative Descriptive Studies: A Systematic Review

MSN, CRNP, Doctoral Candidate, University of Pennsylvania School of Nursing

Justine S. Sefcik

MS, RN, Doctoral Candidate, University of Pennsylvania School of Nursing

Christine Bradway

PhD, CRNP, FAAN, Associate Professor of Gerontological Nursing, University of Pennsylvania School of Nursing

Qualitative description (QD) is a term that is widely used to describe qualitative studies of health care and nursing-related phenomena. However, limited discussions regarding QD are found in the existing literature. In this systematic review, we identified characteristics of methods and findings reported in research articles published in 2014 whose authors identified the work as QD. After searching and screening, data were extracted from the sample of 55 QD articles and examined to characterize research objectives, design justification, theoretical/philosophical frameworks, sampling and sample size, data collection and sources, data analysis, and presentation of findings. In this review, three primary findings were identified. First, despite inconsistencies, most articles included characteristics consistent with limited, available QD definitions and descriptions. Next, flexibility or variability of methods was common and desirable for obtaining rich data and achieving understanding of a phenomenon. Finally, justification for how a QD approach was chosen and why it would be an appropriate fit for a particular study was limited in the sample and, therefore, in need of increased attention. Based on these findings, recommendations include encouragement to researchers to provide as many details as possible regarding the methods of their QD study so that readers can determine whether the methods used were reasonable and effective in producing useful findings.

Qualitative description (QD) is a label used in qualitative research for studies which are descriptive in nature, particularly for examining health care and nursing-related phenomena ( Polit & Beck, 2009 , 2014 ). QD is a widely cited research tradition and has been identified as important and appropriate for research questions focused on discovering the who, what, and where of events or experiences and gaining insights from informants regarding a poorly understood phenomenon. It is also the label of choice when a straight description of a phenomenon is desired or information is sought to develop and refine questionnaires or interventions ( Neergaard et al., 2009 ; Sullivan-Bolyai et al., 2005 ).

Despite many strengths and frequent citations of its use, limited discussions regarding QD are found in qualitative research textbooks and publications. To the best of our knowledge, only seven articles include specific guidance on how to design, implement, analyze, or report the results of a QD study ( Milne & Oberle, 2005 ; Neergaard, Olesen, Andersen, & Sondergaard, 2009 ; Sandelowski, 2000 , 2010 ; Sullivan-Bolyai, Bova, & Harper, 2005 ; Vaismoradi, Turunen, & Bondas, 2013 ; Willis, Sullivan-Bolyai, Knafl, & Zichi-Cohen, 2016 ). Furthermore, little is known about characteristics of QD as reported in journal-published, nursing-related, qualitative studies. Therefore, the purpose of this systematic review was to describe specific characteristics of methods and findings of studies reported in journal articles (published in 2014) self-labeled as QD. In this review, we did not have a goal to judge whether QD was done correctly but rather to report on the features of the methods and findings.

Features of QD

Several QD design features and techniques have been described in the literature. First, researchers generally draw from a naturalistic perspective and examine a phenomenon in its natural state ( Sandelowski, 2000 ). Second, QD has been described as less theoretical compared to other qualitative approaches ( Neergaard et al., 2009 ), facilitating flexibility in commitment to a theory or framework when designing and conducting a study ( Sandelowski, 2000 , 2010 ). For example, researchers may or may not decide to begin with a theory of the targeted phenomenon and do not need to stay committed to a theory or framework if their investigations take them down another path ( Sandelowski, 2010 ). Third, data collection strategies typically involve individual and/or focus group interviews with minimal to semi-structured interview guides ( Neergaard et al., 2009 ; Sandelowski, 2000 ). Fourth, researchers commonly employ purposeful sampling techniques such as maximum variation sampling which has been described as being useful for obtaining broad insights and rich information ( Neergaard et al., 2009 ; Sandelowski, 2000 ). Fifth, content analysis (and in many cases, supplemented by descriptive quantitative data to describe the study sample) is considered a primary strategy for data analysis ( Neergaard et al., 2009 ; Sandelowski, 2000 ). In some instances thematic analysis may also be used to analyze data; however, experts suggest care should be taken that this type of analysis is not confused with content analysis ( Vaismoradi et al., 2013 ). These data analysis approaches allow researchers to stay close to the data and as such, interpretation is of low-inference ( Neergaard et al., 2009 ), meaning that different researchers will agree more readily on the same findings even if they do not choose to present the findings in the same way ( Sandelowski, 2000 ). Finally, representation of study findings in published reports is expected to be straightforward, including comprehensive descriptive summaries and accurate details of the data collected, and presented in a way that makes sense to the reader ( Neergaard et al., 2009 ; Sandelowski, 2000 ).

It is also important to acknowledge that variations in methods or techniques may be appropriate across QD studies ( Sandelowski, 2010 ). For example, when consistent with the study goals, decisions may be made to use techniques from other qualitative traditions, such as employing a constant comparative analytic approach typically associated with grounded theory ( Sandelowski, 2000 ).

Search Strategy and Study Screening

The PubMed electronic database was searched for articles written in English and published from January 1, 2014 to December 31, 2014, using the terms, “qualitative descriptive study,” “qualitative descriptive design,” and “qualitative description,” combined with “nursing.” This specific publication year, “2014,” was chosen because it was the most recent full year at the time of beginning this systematic review. As we did not intend to identify trends in QD approaches over time, it seemed reasonable to focus on the nursing QD studies published in a certain year. The inclusion criterion for this review was data-based, nursing-related, research articles in which authors used the terms QD, qualitative descriptive study, or qualitative descriptive design in their titles or abstracts as well as in the main texts of the publication.

All articles yielded through an initial search in PubMed were exported into EndNote X7 ( Thomson Reuters, 2014 ), a reference management software, and duplicates were removed. Next, titles and abstracts were reviewed to determine if the publication met inclusion criteria; all articles meeting inclusion criteria were then read independently in full by two authors (HK and JS) to determine if the terms – QD or qualitative descriptive study/design – were clearly stated in the main texts. Any articles in which researchers did not specifically state these key terms in the main text were then excluded, even if the terms had been used in the study title or abstract. In one article, for example, although “qualitative descriptive study” was reported in the published abstract, the researchers reported a “qualitative exploratory design” in the main text of the article ( Sundqvist & Carlsson, 2014 ); therefore, this article was excluded from our review. Despite the possibility that there may be other QD studies published in 2014 that were not labeled as such, to facilitate our screening process we only included articles where the researchers clearly used our search terms for their approach. Finally, the two authors compared, discussed, and reconciled their lists of articles with a third author (CB).

Study Selection

Initially, although the year 2014 was specifically requested, 95 articles were identified (due to ahead of print/Epub) and exported into the EndNote program. Three duplicate publications were removed and the 20 articles with final publication dates of 2015 were also excluded. The remaining 72 articles were then screened by examining titles, abstracts, and full-texts. Based on our inclusion criteria, 15 (of 72) were then excluded because QD or QD design/study was not identified in the main text. We then re-examined the remaining 57 articles and excluded two additional articles that did not meet inclusion criteria (e.g., QD was only reported as an analytic approach in the data analysis section). The remaining 55 publications met inclusion criteria and comprised the sample for our systematic review (see Figure 1 ).

Flow Diagram of Study Selection

Of the 55 publications, 23 originated from North America (17 in the United States; 6 in Canada), 12 from Asia, 11 from Europe, 7 from Australia and New Zealand, and 2 from South America. Eleven studies were part of larger research projects and two of them were reported as part of larger mixed-methods studies. Four were described as a secondary analysis.

Quality Appraisal Process

Following the identification of the 55 publications, two authors (HK and JS) independently examined each article using the Critical Appraisal Skills Programme (CASP) qualitative checklist ( CASP, 2013 ). The CASP was chosen to determine the general adequacy (or rigor) of the qualitative studies included in this review as the CASP criteria are generic and intend to be applied to qualitative studies in general. In addition, the CASP was useful because we were able to examine the internal consistency between study aims and methods and between study aims and findings as well as the usefulness of findings ( CASP, 2013 ). The CASP consists of 10 main questions with several sub-questions to consider when making a decision about the main question ( CASP, 2013 ). The first two questions have reviewers examine the clarity of study aims and appropriateness of using qualitative research to achieve the aims. With the next eight questions, reviewers assess study design, sampling, data collection, and analysis as well as the clarity of the study’s results statement and the value of the research. We used the seven questions and 17 sub-questions related to methods and statement of findings to evaluate the articles. The results of this process are presented in Table 1 .

CASP Questions and Quality Appraisal Results (N = 55)

Note . The CASP questions are adapted from “10 questions to help you make sense of qualitative research,” by Critical Appraisal Skills Programme, 2013, retrieved from http://media.wix.com/ugd/dded87_29c5b002d99342f788c6ac670e49f274.pdf . Its license can be found at http://creativecommons.org/licenses/by-nc-sa/3.0/

Once articles were assessed by the two authors independently, all three authors discussed and reconciled our assessment. No articles were excluded based on CASP results; rather, results were used to depict the general adequacy (or rigor) of all 55 articles meeting inclusion criteria for our systematic review. In addition, the CASP was included to enhance our examination of the relationship between the methods and the usefulness of the findings documented in each of the QD articles included in this review.

Process for Data Extraction and Analysis

To further assess each of the 55 articles, data were extracted on: (a) research objectives, (b) design justification, (c) theoretical or philosophical framework, (d) sampling and sample size, (e) data collection and data sources, (f) data analysis, and (g) presentation of findings (see Table 2 ). We discussed extracted data and identified common and unique features in the articles included in our systematic review. Findings are described in detail below and in Table 3 .

Elements for Data Extraction

Data Extraction and Analysis Results

Note . NR = not reported

Quality Appraisal Results

Justification for use of a QD design was evident in close to half (47.3%) of the 55 publications. While most researchers clearly described recruitment strategies (80%) and data collection methods (100%), justification for how the study setting was selected was only identified in 38.2% of the articles and almost 75% of the articles did not include any reason for the choice of data collection methods (e.g., focus-group interviews). In the vast majority (90.9%) of the articles, researchers did not explain their involvement and positionality during the process of recruitment and data collection or during data analysis (63.6%). Ethical standards were reported in greater than 89% of all articles and most articles included an in-depth description of data analysis (83.6%) and development of categories or themes (92.7%). Finally, all researchers clearly stated their findings in relation to research questions/objectives. Researchers of 83.3% of the articles discussed the credibility of their findings (see Table 1 ).

Research Objectives

In statements of study objectives and/or questions, the most frequently used verbs were “explore” ( n = 22) and “describe” ( n = 17). Researchers also used “identify” ( n = 3), “understand” ( n = 4), or “investigate” ( n = 2). Most articles focused on participants’ experiences related to certain phenomena ( n = 18), facilitators/challenges/factors/reasons ( n = 14), perceptions about specific care/nursing practice/interventions ( n = 11), and knowledge/attitudes/beliefs ( n = 3).

Design Justification

A total of 30 articles included references for QD. The most frequently cited references ( n = 23) were “Whatever happened to qualitative description?” ( Sandelowski, 2000 ) and “What’s in a name? Qualitative description revisited” ( Sandelowski, 2010 ). Other references cited included “Qualitative description – the poor cousin of health research?” ( Neergaard et al., 2009 ), “Reaching the parts other methods cannot reach: an introduction to qualitative methods in health and health services research” ( Pope & Mays, 1995 ), and general research textbooks ( Polit & Beck, 2004 , 2012 ).

In 26 articles (and not necessarily the same as those citing specific references to QD), researchers provided a rationale for selecting QD. Most researchers chose QD because this approach aims to produce a straight description and comprehensive summary of the phenomenon of interest using participants’ language and staying close to the data (or using low inference).

Authors of two articles distinctly stated a QD design, yet also acknowledged grounded-theory or phenomenological overtones by adopting some techniques from these qualitative traditions ( Michael, O'Callaghan, Baird, Hiscock, & Clayton, 2014 ; Peacock, Hammond-Collins, & Forbes, 2014 ). For example, Michael et al. (2014 , p. 1066) reported:

The research used a qualitative descriptive design with grounded theory overtones ( Sandelowski, 2000 ). We sought to provide a comprehensive summary of participants’ views through theoretical sampling; multiple data sources (focus groups [FGs] and interviews); inductive, cyclic, and constant comparative analysis; and condensation of data into thematic representations ( Corbin & Strauss, 1990 , 2008 ).

Authors of four additional articles included language suggestive of a grounded-theory or phenomenological tradition, e.g., by employing a constant comparison technique or translating themes stated in participants’ language into the primary language of the researchers during data analysis ( Asemani et al., 2014 ; Li, Lee, Chen, Jeng, & Chen, 2014 ; Ma, 2014 ; Soule, 2014 ). Additionally, Li et al. (2014) specifically reported use of a grounded-theory approach.

Theoretical or Philosophical Framework

In most (n = 48) articles, researchers did not specify any theoretical or philosophical framework. Of those articles in which a framework or philosophical stance was included, the authors of five articles described the framework as guiding the development of an interview guide ( Al-Zadjali, Keller, Larkey, & Evans, 2014 ; DeBruyn, Ochoa-Marin, & Semenic, 2014 ; Fantasia, Sutherland, Fontenot, & Ierardi, 2014 ; Ma, 2014 ; Wiens, Babenko-Mould, & Iwasiw, 2014 ). In two articles, data analysis was described as including key concepts of a framework being used as pre-determined codes or categories ( Al-Zadjali et al., 2014 ; Wiens et al., 2014 ). Oosterveld-Vlug et al. (2014) and Zhang, Shan, and Jiang (2014) discussed a conceptual model and underlying philosophy in detail in the background or discussion section, although the model and philosophy were not described as being used in developing interview questions or analyzing data.

Sampling and Sample Size

In 38 of the 55 articles, researchers reported ‘purposeful sampling’ or some derivation of purposeful sampling such as convenience ( n = 10), maximum variation ( n = 8), snowball ( n = 3), and theoretical sampling ( n = 1). In three instances ( Asemani et al., 2014 ; Chan & Lopez, 2014 ; Soule, 2014 ), multiple sampling strategies were described, for example, a combination of snowball, convenience, and maximum variation sampling. In articles where maximum variation sampling was employed, “variation” referred to seeking diversity in participants’ demographics ( n = 7; e.g., age, gender, and education level), while one article did not include details regarding how their maximum variation sampling strategy was operationalized ( Marcinowicz, Abramowicz, Zarzycka, Abramowicz, & Konstantynowicz, 2014 ). Authors of 17 articles did not specify their sampling techniques.

Sample sizes ranged from 8 to 1,932 with nine studies in the 8–10 participant range and 24 studies in the 11–20 participant range. The participant range of 21–30 and 31–50 was reported in eight articles each. Six studies included more than 50 participants. Two of these articles depicted quite large sample sizes (N=253, Hart & Mareno, 2014 ; N=1,932, Lyndon et al., 2014 ) and the authors of these articles described the use of survey instruments and analysis of responses to open-ended questions. This was in contrast to studies with smaller sample sizes where individual interviews and focus groups were more commonly employed.

Data Collection and Data Sources

In a majority of studies, researchers collected data through individual ( n = 39) and/or focus-group ( n = 14) interviews that were semistructured. Most researchers reported that interviews were audiotaped ( n = 51) and interview guides were described as the primary data collection tool in 29 of the 51 studies. In some cases, researchers also described additional data sources, for example, taking memos or field notes during participant observation sessions or as a way to reflect their thoughts about interviews ( n = 10). Written responses to open-ended questions in survey questionnaires were another type of data source in a small number of studies ( n = 4).

Data Analysis

The analysis strategy most commonly used in the QD studies included in this review was qualitative content analysis ( n = 30). Among the studies where this technique was used, most researchers described an inductive approach; researchers of two studies analyzed data both inductively and deductively. Thematic analysis was adopted in 14 studies and the constant comparison technique in 10 studies. In nine studies, researchers employed multiple techniques to analyze data including qualitative content analysis with constant comparison ( Asemani et al., 2014 ; DeBruyn et al., 2014 ; Holland, Christensen, Shone, Kearney, & Kitzman, 2014 ; Li et al., 2014 ) and thematic analysis with constant comparison ( Johansson, Hildingsson, & Fenwick, 2014 ; Oosterveld-Vlug et al., 2014 ). In addition, five teams conducted descriptive statistical analysis using both quantitative and qualitative data and counting the frequencies of codes/themes ( Ewens, Chapman, Tulloch, & Hendricks, 2014 ; Miller, 2014 ; Santos, Sandelowski, & Gualda, 2014 ; Villar, Celdran, Faba, & Serrat, 2014 ) or targeted events through video monitoring ( Martorella, Boitor, Michaud, & Gelinas, 2014 ). Tseng, Chen, and Wang (2014) cited Thorne, Reimer Kirkham, and O’Flynn-Magee (2004)’s interpretive description as the inductive analytic approach. In five out of 55 articles, researchers did not specifically name their analysis strategies, despite including descriptions about procedural aspects of data analysis. Researchers of 20 studies reported that data saturation for their themes was achieved.

Presentation of Findings

Researchers described participants’ experiences of health care, interventions, or illnesses in 18 articles and presented straightforward, focused, detailed descriptions of facilitators, challenges, factors, reasons, and causes in 15 articles. Participants’ perceptions of specific care, interventions, or programs were described in detail in 11 articles. All researchers presented their findings with extensive descriptions including themes or categories. In 25 of 55 articles, figures or tables were also presented to illustrate or summarize the findings. In addition, the authors of three articles summarized, organized, and described their data using key concepts of conceptual models ( Al-Zadjali et al., 2014 ; Oosterveld-Vlug et al., 2014 ; Wiens et al., 2014 ). Martorella et al. (2014) assessed acceptability and feasibility of hand massage therapy and arranged their findings in relation to pre-determined indicators of acceptability and feasibility. In one longitudinal QD study ( Kneck, Fagerberg, Eriksson, & Lundman, 2014 ), the researchers presented the findings as several key patterns of learning for persons living with diabetes; in another longitudinal QD study ( Stegenga & Macpherson, 2014 ), findings were presented as processes and themes regarding patients’ identity work across the cancer trajectory. In another two studies, the researchers described and compared themes or categories from two different perspectives, such as patients and nurses ( Canzan, Heilemann, Saiani, Mortari, & Ambrosi, 2014 ) or parents and children ( Marcinowicz et al., 2014 ). Additionally, Ma (2014) reported themes using both participants’ language and the researcher’s language.

In this systematic review, we examined and reported specific characteristics of methods and findings reported in journal articles self-identified as QD and published during one calendar year. To accomplish this we identified 55 articles that met inclusion criteria, performed a quality appraisal following CASP guidelines, and extracted and analyzed data focusing on QD features. In general, three primary findings emerged. First, despite inconsistencies, most QD publications had the characteristics that were originally observed by Sandelowski (2000) and summarized by other limited available QD literature. Next, there are no clear boundaries in methods used in the QD studies included in this review; in a number of studies, researchers adopted and combined techniques originating from other qualitative traditions to obtain rich data and increase their understanding of the phenomenon under investigation. Finally, justification for how QD was chosen and why it would be an appropriate fit for a particular study is an area in need of increased attention.

In general, the overall characteristics were consistent with design features of QD studies described in the literature ( Neergaard et al., 2009 ; Sandelowski, 2000 , 2010 ; Vaismoradi et al., 2013 ). For example, many authors reported that study objectives were to describe or explore participants’ experiences and factors related to certain phenomena, events, or interventions. In most cases, these authors cited Sandelowski (2000) as a reference for this particular characteristic. It was rare that theoretical or philosophical frameworks were identified, which also is consistent with descriptions of QD. In most studies, researchers used purposeful sampling and its derivative sampling techniques, collected data through interviews, and analyzed data using qualitative content analysis or thematic analysis. Moreover, all researchers presented focused or comprehensive, descriptive summaries of data including themes or categories answering their research questions. These characteristics do not indicate that there are correct ways to do QD studies; rather, they demonstrate how others designed and produced QD studies.

In several studies, researchers combined techniques that originated from other qualitative traditions for sampling, data collection, and analysis. This flexibility or variability, a key feature of recently published QD studies, may indicate that there are no clear boundaries in designing QD studies. Sandelowski (2010) articulated: “in the actual world of research practice, methods bleed into each other; they are so much messier than textbook depictions” (p. 81). Hammersley (2007) also observed:

“We are not so much faced with a set of clearly differentiated qualitative approaches as with a complex landscape of variable practice in which the inhabitants use a range of labels (‘ethnography’, ‘discourse analysis’, ‘life history work’, narrative study’, ……, and so on) in diverse and open-ended ways in order to characterize their orientation, and probably do this somewhat differently across audiences and occasions” (p. 293).

This concept of having no clear boundaries in methods when designing a QD study should enable researchers to obtain rich data and produce a comprehensive summary of data through various data collection and analysis approaches to answer their research questions. For example, using an ethnographical approach (e.g., participant observation) in data collection for a QD study may facilitate an in-depth description of participants’ nonverbal expressions and interactions with others and their environment as well as situations or events in which researchers are interested ( Kawulich, 2005 ). One example found in our review is that Adams et al. (2014) explored family members’ responses to nursing communication strategies for patients in intensive care units (ICUs). In this study, researchers conducted interviews with family members, observed interactions between healthcare providers, patients, and family members in ICUs, attended ICU rounds and family meetings, and took field notes about their observations and reflections. Accordingly, the variability in methods provided Adams and colleagues (2014) with many different aspects of data that were then used to complement participants’ interviews (i.e., data triangulation). Moreover, by using a constant comparison technique in addition to qualitative content analysis or thematic analysis in QD studies, researchers compare each case with others looking for similarities and differences as well as reasoning why differences exist, to generate more general understanding of phenomena of interest ( Thorne, 2000 ). In fact, this constant comparison analysis is compatible with qualitative content analysis and thematic analysis and we found several examples of using this approach in studies we reviewed ( Asemani et al., 2014 ; DeBruyn et al., 2014 ; Holland et al., 2014 ; Johansson et al., 2014 ; Li et al., 2014 ; Oosterveld-Vlug et al., 2014 ).

However, this flexibility or variability in methods of QD studies may cause readers’ as well as researchers’ confusion in designing and often labeling qualitative studies ( Neergaard et al., 2009 ). Especially, it could be difficult for scholars unfamiliar with qualitative studies to differentiate QD studies with “hues, tones, and textures” of qualitative traditions ( Sandelowski, 2000 , p. 337) from grounded theory, phenomenological, and ethnographical research. In fact, the major difference is in the presentation of the findings (or outcomes of qualitative research) ( Neergaard et al., 2009 ; Sandelowski, 2000 ). The final products of grounded theory, phenomenological, and ethnographical research are a generation of a theory, a description of the meaning or essence of people’s lived experience, and an in-depth, narrative description about certain culture, respectively, through researchers’ intensive/deep interpretations, reflections, and/or transformation of data ( Streubert & Carpenter, 2011 ). In contrast, QD studies result in “a rich, straight description” of experiences, perceptions, or events using language from the collected data ( Neergaard et al., 2009 ) through low-inference (or data-near) interpretations during data analysis ( Sandelowski, 2000 , 2010 ). This feature is consistent with our finding regarding presentation of findings: in all QD articles included in this systematic review, the researchers presented focused or comprehensive, descriptive summaries to their research questions.

Finally, an explanation or justification of why a QD approach was chosen or appropriate for the study aims was not found in more than half of studies in the sample. While other qualitative approaches, including grounded theory, phenomenology, ethnography, and narrative analysis, are used to better understand people’s thoughts, behaviors, and situations regarding certain phenomena ( Sullivan-Bolyai et al., 2005 ), as noted above, the results will likely read differently than those for a QD study ( Carter & Little, 2007 ). Therefore, it is important that researchers accurately label and justify their choices of approach, particularly for studies focused on participants’ experiences, which could be addressed with other qualitative traditions. Justifying one’s research epistemology, methodology, and methods allows readers to evaluate these choices for internal consistency, provides context to assist in understanding the findings, and contributes to the transparency of choices, all of which enhance the rigor of the study ( Carter & Little, 2007 ; Wu, Thompson, Aroian, McQuaid, & Deatrick, 2016 ).

Use of the CASP tool drew our attention to the credibility and usefulness of the findings of the QD studies included in this review. Although justification for study design and methods was lacking in many articles, most authors reported techniques of recruitment, data collection, and analysis that appeared. Internal consistencies among study objectives, methods, and findings were achieved in most studies, increasing readers’ confidence that the findings of these studies are credible and useful in understanding under-explored phenomenon of interest.

In summary, our findings support the notion that many scholars employ QD and include a variety of commonly observed characteristics in their study design and subsequent publications. Based on our review, we found that QD as a scholarly approach allows flexibility as research questions and study findings emerge. We encourage authors to provide as many details as possible regarding how QD was chosen for a particular study as well as details regarding methods to facilitate readers’ understanding and evaluation of the study design and rigor. We acknowledge the challenge of strict word limitation with submissions to print journals; potential solutions include collaboration with journal editors and staff to consider creative use of charts or tables, or using more citations and less text in background sections so that methods sections are robust.

Limitations

Several limitations of this review deserve mention. First, only articles where researchers explicitly stated in the main body of the article that a QD design was employed were included. In contrast, articles labeled as QD in only the title or abstract, or without their research design named were not examined due to the lack of certainty that the researchers actually carried out a QD study. As a result, we may have excluded some studies where a QD design was followed. Second, only one database was searched and therefore we did not identify or describe potential studies following a QD approach that were published in non-PubMed databases. Third, our review is limited by reliance on what was included in the published version of a study. In some cases, this may have been a result of word limits or specific styles imposed by journals, or inconsistent reporting preferences of authors and may have limited our ability to appraise the general adequacy with the CASP tool and examine specific characteristics of these studies.

Conclusions

A systematic review was conducted by examining QD research articles focused on nursing-related phenomena and published in one calendar year. Current patterns include some characteristics of QD studies consistent with the previous observations described in the literature, a focus on the flexibility or variability of methods in QD studies, and a need for increased explanations of why QD was an appropriate label for a particular study. Based on these findings, recommendations include encouragement to authors to provide as many details as possible regarding the methods of their QD study. In this way, readers can thoroughly consider and examine if the methods used were effective and reasonable in producing credible and useful findings.

Acknowledgments

This work was supported in part by the John A. Hartford Foundation’s National Hartford Centers of Gerontological Nursing Excellence Award Program.

Hyejin Kim is a Ruth L. Kirschstein NRSA Predoctoral Fellow (F31NR015702) and 2013–2015 National Hartford Centers of Gerontological Nursing Excellence Patricia G. Archbold Scholar. Justine Sefcik is a Ruth L. Kirschstein Predoctoral Fellow (F31NR015693) through the National Institutes of Health, National Institute of Nursing Research.

Conflict of Interest Statement

The Authors declare that there is no conflict of interest.

Contributor Information

Hyejin Kim, MSN, CRNP, Doctoral Candidate, University of Pennsylvania School of Nursing.

Justine S. Sefcik, MS, RN, Doctoral Candidate, University of Pennsylvania School of Nursing.

Christine Bradway, PhD, CRNP, FAAN, Associate Professor of Gerontological Nursing, University of Pennsylvania School of Nursing.

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Understanding Descriptive Research Designs and Methods

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• 1 Author Affiliation: Senior Nurse Scientist and Clinical Nurse Specialist, Office of Nursing Research & Innovation, Nursing Institute, Cleveland Clinic, Ohio.
• PMID: 31789957
• DOI: 10.1097/NUR.0000000000000493

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Home » Descriptive Research Design – Types, Methods and Examples

Descriptive Research Design – Types, Methods and Examples

Table of Contents

Descriptive Research Design

Definition:

Descriptive research design is a type of research methodology that aims to describe or document the characteristics, behaviors, attitudes, opinions, or perceptions of a group or population being studied.

Descriptive research design does not attempt to establish cause-and-effect relationships between variables or make predictions about future outcomes. Instead, it focuses on providing a detailed and accurate representation of the data collected, which can be useful for generating hypotheses, exploring trends, and identifying patterns in the data.

Types of Descriptive Research Design

Types of Descriptive Research Design are as follows:

Cross-sectional Study

This involves collecting data at a single point in time from a sample or population to describe their characteristics or behaviors. For example, a researcher may conduct a cross-sectional study to investigate the prevalence of certain health conditions among a population, or to describe the attitudes and beliefs of a particular group.

Longitudinal Study

This involves collecting data over an extended period of time, often through repeated observations or surveys of the same group or population. Longitudinal studies can be used to track changes in attitudes, behaviors, or outcomes over time, or to investigate the effects of interventions or treatments.

This involves an in-depth examination of a single individual, group, or situation to gain a detailed understanding of its characteristics or dynamics. Case studies are often used in psychology, sociology, and business to explore complex phenomena or to generate hypotheses for further research.

Survey Research

This involves collecting data from a sample or population through standardized questionnaires or interviews. Surveys can be used to describe attitudes, opinions, behaviors, or demographic characteristics of a group, and can be conducted in person, by phone, or online.

Observational Research

This involves observing and documenting the behavior or interactions of individuals or groups in a natural or controlled setting. Observational studies can be used to describe social, cultural, or environmental phenomena, or to investigate the effects of interventions or treatments.

Correlational Research

This involves examining the relationships between two or more variables to describe their patterns or associations. Correlational studies can be used to identify potential causal relationships or to explore the strength and direction of relationships between variables.

Data Analysis Methods

Descriptive research design data analysis methods depend on the type of data collected and the research question being addressed. Here are some common methods of data analysis for descriptive research:

Descriptive Statistics

This method involves analyzing data to summarize and describe the key features of a sample or population. Descriptive statistics can include measures of central tendency (e.g., mean, median, mode) and measures of variability (e.g., range, standard deviation).

Cross-tabulation

This method involves analyzing data by creating a table that shows the frequency of two or more variables together. Cross-tabulation can help identify patterns or relationships between variables.

Content Analysis

This method involves analyzing qualitative data (e.g., text, images, audio) to identify themes, patterns, or trends. Content analysis can be used to describe the characteristics of a sample or population, or to identify factors that influence attitudes or behaviors.

Qualitative Coding

This method involves analyzing qualitative data by assigning codes to segments of data based on their meaning or content. Qualitative coding can be used to identify common themes, patterns, or categories within the data.

Visualization

This method involves creating graphs or charts to represent data visually. Visualization can help identify patterns or relationships between variables and make it easier to communicate findings to others.

Comparative Analysis

This method involves comparing data across different groups or time periods to identify similarities and differences. Comparative analysis can help describe changes in attitudes or behaviors over time or differences between subgroups within a population.

Applications of Descriptive Research Design

Descriptive research design has numerous applications in various fields. Some of the common applications of descriptive research design are:

• Market research: Descriptive research design is widely used in market research to understand consumer preferences, behavior, and attitudes. This helps companies to develop new products and services, improve marketing strategies, and increase customer satisfaction.
• Health research: Descriptive research design is used in health research to describe the prevalence and distribution of a disease or health condition in a population. This helps healthcare providers to develop prevention and treatment strategies.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs. This helps educators to improve teaching methods and develop effective educational programs.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs. This helps researchers to understand social behavior and develop effective policies.
• Public opinion research: Descriptive research design is used in public opinion research to understand the opinions and attitudes of the general public on various issues. This helps policymakers to develop effective policies that are aligned with public opinion.
• Environmental research: Descriptive research design is used in environmental research to describe the environmental conditions of a particular region or ecosystem. This helps policymakers and environmentalists to develop effective conservation and preservation strategies.

Descriptive Research Design Examples

Here are some real-time examples of descriptive research designs:

• A restaurant chain wants to understand the demographics and attitudes of its customers. They conduct a survey asking customers about their age, gender, income, frequency of visits, favorite menu items, and overall satisfaction. The survey data is analyzed using descriptive statistics and cross-tabulation to describe the characteristics of their customer base.
• A medical researcher wants to describe the prevalence and risk factors of a particular disease in a population. They conduct a cross-sectional study in which they collect data from a sample of individuals using a standardized questionnaire. The data is analyzed using descriptive statistics and cross-tabulation to identify patterns in the prevalence and risk factors of the disease.
• An education researcher wants to describe the learning outcomes of students in a particular school district. They collect test scores from a representative sample of students in the district and use descriptive statistics to calculate the mean, median, and standard deviation of the scores. They also create visualizations such as histograms and box plots to show the distribution of scores.
• A marketing team wants to understand the attitudes and behaviors of consumers towards a new product. They conduct a series of focus groups and use qualitative coding to identify common themes and patterns in the data. They also create visualizations such as word clouds to show the most frequently mentioned topics.
• An environmental scientist wants to describe the biodiversity of a particular ecosystem. They conduct an observational study in which they collect data on the species and abundance of plants and animals in the ecosystem. The data is analyzed using descriptive statistics to describe the diversity and richness of the ecosystem.

How to Conduct Descriptive Research Design

To conduct a descriptive research design, you can follow these general steps:

• Define your research question: Clearly define the research question or problem that you want to address. Your research question should be specific and focused to guide your data collection and analysis.
• Choose your research method: Select the most appropriate research method for your research question. As discussed earlier, common research methods for descriptive research include surveys, case studies, observational studies, cross-sectional studies, and longitudinal studies.
• Design your study: Plan the details of your study, including the sampling strategy, data collection methods, and data analysis plan. Determine the sample size and sampling method, decide on the data collection tools (such as questionnaires, interviews, or observations), and outline your data analysis plan.
• Collect data: Collect data from your sample or population using the data collection tools you have chosen. Ensure that you follow ethical guidelines for research and obtain informed consent from participants.
• Analyze data: Use appropriate statistical or qualitative analysis methods to analyze your data. As discussed earlier, common data analysis methods for descriptive research include descriptive statistics, cross-tabulation, content analysis, qualitative coding, visualization, and comparative analysis.
• I nterpret results: Interpret your findings in light of your research question and objectives. Identify patterns, trends, and relationships in the data, and describe the characteristics of your sample or population.
• Draw conclusions and report results: Draw conclusions based on your analysis and interpretation of the data. Report your results in a clear and concise manner, using appropriate tables, graphs, or figures to present your findings. Ensure that your report follows accepted research standards and guidelines.

When to Use Descriptive Research Design

Descriptive research design is used in situations where the researcher wants to describe a population or phenomenon in detail. It is used to gather information about the current status or condition of a group or phenomenon without making any causal inferences. Descriptive research design is useful in the following situations:

• Exploratory research: Descriptive research design is often used in exploratory research to gain an initial understanding of a phenomenon or population.
• Identifying trends: Descriptive research design can be used to identify trends or patterns in a population, such as changes in consumer behavior or attitudes over time.
• Market research: Descriptive research design is commonly used in market research to understand consumer preferences, behavior, and attitudes.
• Health research: Descriptive research design is useful in health research to describe the prevalence and distribution of a disease or health condition in a population.
• Social science research: Descriptive research design is used in social science research to describe social phenomena such as cultural norms, values, and beliefs.
• Educational research: Descriptive research design is used in educational research to describe the performance of students, schools, or educational programs.

Purpose of Descriptive Research Design

The main purpose of descriptive research design is to describe and measure the characteristics of a population or phenomenon in a systematic and objective manner. It involves collecting data that describe the current status or condition of the population or phenomenon of interest, without manipulating or altering any variables.

The purpose of descriptive research design can be summarized as follows:

• To provide an accurate description of a population or phenomenon: Descriptive research design aims to provide a comprehensive and accurate description of a population or phenomenon of interest. This can help researchers to develop a better understanding of the characteristics of the population or phenomenon.
• To identify trends and patterns: Descriptive research design can help researchers to identify trends and patterns in the data, such as changes in behavior or attitudes over time. This can be useful for making predictions and developing strategies.
• To generate hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• To establish a baseline: Descriptive research design can establish a baseline or starting point for future research. This can be useful for comparing data from different time periods or populations.

Characteristics of Descriptive Research Design

Descriptive research design has several key characteristics that distinguish it from other research designs. Some of the main characteristics of descriptive research design are:

• Objective : Descriptive research design is objective in nature, which means that it focuses on collecting factual and accurate data without any personal bias. The researcher aims to report the data objectively without any personal interpretation.
• Non-experimental: Descriptive research design is non-experimental, which means that the researcher does not manipulate any variables. The researcher simply observes and records the behavior or characteristics of the population or phenomenon of interest.
• Quantitative : Descriptive research design is quantitative in nature, which means that it involves collecting numerical data that can be analyzed using statistical techniques. This helps to provide a more precise and accurate description of the population or phenomenon.
• Cross-sectional: Descriptive research design is often cross-sectional, which means that the data is collected at a single point in time. This can be useful for understanding the current state of the population or phenomenon, but it may not provide information about changes over time.
• Large sample size: Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Systematic and structured: Descriptive research design involves a systematic and structured approach to data collection, which helps to ensure that the data is accurate and reliable. This involves using standardized procedures for data collection, such as surveys, questionnaires, or observation checklists.

Advantages of Descriptive Research Design

Descriptive research design has several advantages that make it a popular choice for researchers. Some of the main advantages of descriptive research design are:

• Provides an accurate description: Descriptive research design is focused on accurately describing the characteristics of a population or phenomenon. This can help researchers to develop a better understanding of the subject of interest.
• Easy to conduct: Descriptive research design is relatively easy to conduct and requires minimal resources compared to other research designs. It can be conducted quickly and efficiently, and data can be collected through surveys, questionnaires, or observations.
• Useful for generating hypotheses: Descriptive research design can be used to generate hypotheses or research questions that can be tested in future studies. For example, if a descriptive study finds a correlation between two variables, this could lead to the development of a hypothesis about the causal relationship between the variables.
• Large sample size : Descriptive research design typically involves a large sample size, which helps to ensure that the data is representative of the population of interest. A large sample size also helps to increase the reliability and validity of the data.
• Can be used to monitor changes : Descriptive research design can be used to monitor changes over time in a population or phenomenon. This can be useful for identifying trends and patterns, and for making predictions about future behavior or attitudes.
• Can be used in a variety of fields : Descriptive research design can be used in a variety of fields, including social sciences, healthcare, business, and education.

Limitation of Descriptive Research Design

Descriptive research design also has some limitations that researchers should consider before using this design. Some of the main limitations of descriptive research design are:

• Cannot establish cause and effect: Descriptive research design cannot establish cause and effect relationships between variables. It only provides a description of the characteristics of the population or phenomenon of interest.
• Limited generalizability: The results of a descriptive study may not be generalizable to other populations or situations. This is because descriptive research design often involves a specific sample or situation, which may not be representative of the broader population.
• Potential for bias: Descriptive research design can be subject to bias, particularly if the researcher is not objective in their data collection or interpretation. This can lead to inaccurate or incomplete descriptions of the population or phenomenon of interest.
• Limited depth: Descriptive research design may provide a superficial description of the population or phenomenon of interest. It does not delve into the underlying causes or mechanisms behind the observed behavior or characteristics.
• Limited utility for theory development: Descriptive research design may not be useful for developing theories about the relationship between variables. It only provides a description of the variables themselves.
• Relies on self-report data: Descriptive research design often relies on self-report data, such as surveys or questionnaires. This type of data may be subject to biases, such as social desirability bias or recall bias.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Survey descriptive research: Method, design, and examples

• November 2, 2022

What is survey descriptive research?

The observational method: monitor people while they engage with a subject, the case study method: gain an in-depth understanding of a subject, survey descriptive research: easy and cost-effective, types of descriptive research design, what is the descriptive survey research design definition by authors, 1. quantitativeness and qualitatively, 2. uncontrolled variables, 3. natural environment, 4. provides a solid basis for further research, describe a group and define its characteristics, measure data trends by conducting descriptive marketing research, understand how customers perceive a brand, descriptive survey research design: how to make the best descriptive questionnaire, create descriptive surveys with surveyplanet.

Survey descriptive research is a quantitative method that focuses on describing the characteristics of a phenomenon rather than asking why it occurs. Doing this provides a better understanding of the nature of the subject at hand and creates a good foundation for further research.

Descriptive market research is one of the most commonly used ways of examining trends and changes in the market. It is easy, low-cost, and provides valuable in-depth information on a chosen subject.

This article will examine the basic principles of the descriptive survey study and show how to make the best descriptive survey questionnaire and how to conduct effective research.

It is often said to be quantitative research that focuses more on the what, how, when, and where instead of the why. But what does that actually mean?

The answer is simple. By conducting descriptive survey research, the nature of a phenomenon is focused upon without asking about what causes it.

The main goal of survey descriptive research is to shed light on the heart of the research problem and better understand it. The technique provides in-depth knowledge of what the research problem is before investigating why it exists.

Survey descriptive research and data collection methods

Descriptive research methods can differ based on data collection. We distinguish three main data collection methods: case study, observational method, and descriptive survey method.

Of these, the descriptive survey research method is most commonly used in fields such as market research, social research, psychology, politics, etc.

Sometimes also called the observational descriptive method, this is simply monitoring people while they engage with a particular subject. The aim is to examine people’s real-life behavior by maintaining a natural environment that does not change the respondents’ behavior—because they do not know they are being observed.

It is often used in fields such as market research, psychology, or social research. For example, customers can be monitored while dining at a restaurant or browsing through the products in a shop.

When doing case studies, researchers conduct thorough examinations of individuals or groups. The case study method is not used to collect general information on a particular subject. Instead, it provides an in-depth understanding of a particular subject and can give rise to interesting conclusions and new hypotheses.

The term case study can also refer to a sample group, which is a specific group of people that are examined and, afterward, findings are generalized to a larger group of people. However, this kind of generalization is rather risky because it is not always accurate.

Additionally, case studies cannot be used to determine cause and effect because of potential bias on the researcher’s part.

The survey descriptive research method consists of creating questionnaires or polls and distributing them to respondents, who then answer the questions (usually a mix of open-ended and closed-ended).

Surveys are the easiest and most cost-efficient way to gain feedback on a particular topic. They can be conducted online or offline, the size of the sample is highly flexible, and they can be distributed through many different channels.

When doing market research , use such surveys to understand the demographic of a certain market or population, better determine the target audience, keep track of the changes in the market, and learn about customer experience and satisfaction with products and services.

Several types of survey descriptive research are classified based on the approach used:

• Descriptive surveys gather information about a certain subject.
• Descriptive-normative surveys gather information just like a descriptive survey, after which results are compared with a norm.
• Correlative surveys explore the relationship between two variables and conclude if it is positive, neutral, or negative.

A descriptive survey research design is a methodology used in social science and other fields to gather information and describe the characteristics, behaviors, or attitudes of a particular population or group of interest. While there may not be a single definition provided by specific authors, the concept is widely understood and defined similarly across the literature.

Here’s a general definition that captures the essence of a descriptive survey research design definition by authors:

A descriptive survey research design is a systematic and structured approach to collecting data from a sample of individuals or entities within a larger population, with the primary aim of providing a detailed and accurate description of the characteristics, behaviors, opinions, or attitudes that exist within the target group. This method involves the use of surveys, questionnaires, interviews, or observations to collect data, which is then analyzed and summarized to draw conclusions about the population of interest.

It’s important to note that descriptive survey research is often used when researchers want to gain insights into a population or phenomenon, but without manipulating variables or testing hypotheses, as is common in experimental research. Instead, it focuses on providing a comprehensive overview of the subject under investigation. Researchers often use various statistical and analytical techniques to summarize and interpret the collected data in descriptive survey research.

The characteristics and advantages of a descriptive survey questionnaire

There are numerous advantages to using a descriptive survey design. First of all, it is cheap and easy to conduct. A large sample can be surveyed and extensive data gathered quickly and inexpensively.

The data collected provides both quantitative and qualitative information , which provides a holistic understanding of the topic. Moreover, it can be used in further research on this or related topics.

Here are some of the most important advantages of conducting a survey descriptive research:

The descriptive survey research design uses both quantitative and qualitative research methods. It is used primarily to conduct quantitative research and gather data that is statistically easy to analyze. However, it can also provide qualitative data that helps describe and understand the research subject.

Descriptive research explores more than one variable. However, unlike experimental research, descriptive survey research design doesn’t allow control of variables. Instead, observational methods are used during research. Even though these variables can change and have an unexpected impact on an inquiry, they will give access to honest responses.

The descriptive research is conducted in a natural environment. This way, answers gathered from responses are more honest because the nature of the research does not influence them.

The data collected through descriptive research can be used to further explore the same or related subjects. Additionally, it can help develop the next line of research and the best method to use moving forward.

Descriptive survey example: When to use a descriptive research questionnaire?

Descriptive research design can be used for many purposes. It is mainly utilized to test a hypothesis, define the characteristics of a certain phenomenon, and examine the correlations between them.

Market research is one of the main fields in which descriptive methods are used to conduct studies. Here’s what can be done using this method:

Understanding the needs of customers and their desires is the key to a business’s success. By truly understanding these, it will be possible to offer exactly what customers need and prevent them from turning to competitors.

By using a descriptive survey, different customer characteristics—such as traits, opinions, or behavior patterns—can be determined. With this data, different customer types can be defined and profiles developed that focus on their interests and the behavior they exhibit. This information can be used to develop new products and services that will be successful.

Measuring data trends is extremely important. Explore the market and get valuable insights into how consumers’ interests change over time—as well as how the competition is performing in the marketplace.

Over time, the data gathered from a descriptive questionnaire can be subjected to statistical analysis. This will deliver valuable insights.

Another important aspect to consider is brand awareness. People need to know about your brand, and they need to have a positive opinion of it. The best way to discover their perception is to conduct a brand survey , which gives deeper insight into brand awareness, perception, identity, and customer loyalty .

When conducting survey descriptive research, there are a few basic steps that are needed for a survey to be successful:

• Define the research goals.
• Decide on the research method.
• Define the sample population.
• Design the questionnaire.
• Write specific questions.
• Distribute the questionnaire.
• Analyze the data .
• Make a survey report.

First of all, define the research goals. By setting up clear objectives, every other step can be worked through. This will result in the perfect descriptive questionnaire example and collect only valuable data.

Next, decide on the research method to use—in this case, the descriptive survey method. Then, define the sample population for (that is, the target audience). After that, think about the design itself and the questions that will be asked in the survey .

If you’re not sure where to start, we’ve got you covered. As free survey software, SurveyPlanet offers pre-made themes that are clean and eye-catching, as well as pre-made questions that will save you the trouble of making new ones.

Simply scroll through our library and choose a descriptive survey questionnaire sample that best suits your needs, though our user-friendly interface can help you create bespoke questions in a process that is easy and efficient.

With a survey in hand, it will then need to be delivered to the target audience. This is easy with our survey embedding feature, which allows for the linking of surveys on a website, via emails, or by sharing on social media.

When all the responses are gathered, it’s time to analyze them. Use SurveyPlanet to easily filter data and do cross-sectional analysis. Finally, just export the results and make a survey report.

Conducting descriptive survey research is the best way to gain a deeper knowledge of a topic of interest and develop a sound basis for further research. Sign up for a free SurveyPlanet account to start improving your business today!

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Descriptive Research and Qualitative Research

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• Eunsook T. Koh 2 &
• Willis L. Owen 2  

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Descriptive research is a study of status and is widely used in education, nutrition, epidemiology, and the behavioral sciences. Its value is based on the premise that problems can be solved and practices improved through observation, analysis, and description. The most common descriptive research method is the survey, which includes questionnaires, personal interviews, phone surveys, and normative surveys. Developmental research is also descriptive. Through cross-sectional and longitudinal studies, researchers investigate the interaction of diet (e.g., fat and its sources, fiber and its sources, etc.) and life styles (e.g., smoking, alcohol drinking, etc.) and of disease (e.g., cancer, coronary heart disease) development. Observational research and correlational studies constitute other forms of descriptive research. Correlational studies determine and analyze relationships between variables as well as generate predictions. Descriptive research generates data, both qualitative and quantitative, that define the state of nature at a point in time. This chapter discusses some characteristics and basic procedures of the various types of descriptive research.

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Home Market Research

Descriptive Research: Definition, Characteristics, Methods + Examples

Suppose an apparel brand wants to understand the fashion purchasing trends among New York’s buyers, then it must conduct a demographic survey of the specific region, gather population data, and then conduct descriptive research on this demographic segment.

The study will then uncover details on “what is the purchasing pattern of New York buyers,” but will not cover any investigative information about “ why ” the patterns exist. Because for the apparel brand trying to break into this market, understanding the nature of their market is the study’s main goal. Let’s talk about it.

What is descriptive research?

Descriptive research is a research method describing the characteristics of the population or phenomenon studied. This descriptive methodology focuses more on the “what” of the research subject than the “why” of the research subject.

The method primarily focuses on describing the nature of a demographic segment without focusing on “why” a particular phenomenon occurs. In other words, it “describes” the research subject without covering “why” it happens.

Characteristics of descriptive research

The term descriptive research then refers to research questions, the design of the study, and data analysis conducted on that topic. We call it an observational research method because none of the research study variables are influenced in any capacity.

Some distinctive characteristics of descriptive research are:

• Quantitative research: It is a quantitative research method that attempts to collect quantifiable information for statistical analysis of the population sample. It is a popular market research tool that allows us to collect and describe the demographic segment’s nature.
• Uncontrolled variables: In it, none of the variables are influenced in any way. This uses observational methods to conduct the research. Hence, the nature of the variables or their behavior is not in the hands of the researcher.
• Cross-sectional studies: It is generally a cross-sectional study where different sections belonging to the same group are studied.
• The basis for further research: Researchers further research the data collected and analyzed from descriptive research using different research techniques. The data can also help point towards the types of research methods used for the subsequent research.

Applications of descriptive research with examples

A descriptive research method can be used in multiple ways and for various reasons. Before getting into any survey , though, the survey goals and survey design are crucial. Despite following these steps, there is no way to know if one will meet the research outcome. How to use descriptive research? To understand the end objective of research goals, below are some ways organizations currently use descriptive research today:

• Define respondent characteristics: The aim of using close-ended questions is to draw concrete conclusions about the respondents. This could be the need to derive patterns, traits, and behaviors of the respondents. It could also be to understand from a respondent their attitude, or opinion about the phenomenon. For example, understand millennials and the hours per week they spend browsing the internet. All this information helps the organization researching to make informed business decisions.
• Measure data trends: Researchers measure data trends over time with a descriptive research design’s statistical capabilities. Consider if an apparel company researches different demographics like age groups from 24-35 and 36-45 on a new range launch of autumn wear. If one of those groups doesn’t take too well to the new launch, it provides insight into what clothes are like and what is not. The brand drops the clothes and apparel that customers don’t like.
• Conduct comparisons: Organizations also use a descriptive research design to understand how different groups respond to a specific product or service. For example, an apparel brand creates a survey asking general questions that measure the brand’s image. The same study also asks demographic questions like age, income, gender, geographical location, geographic segmentation , etc. This consumer research helps the organization understand what aspects of the brand appeal to the population and what aspects do not. It also helps make product or marketing fixes or even create a new product line to cater to high-growth potential groups.
• Validate existing conditions: Researchers widely use descriptive research to help ascertain the research object’s prevailing conditions and underlying patterns. Due to the non-invasive research method and the use of quantitative observation and some aspects of qualitative observation , researchers observe each variable and conduct an in-depth analysis . Researchers also use it to validate any existing conditions that may be prevalent in a population.
• Conduct research at different times: The analysis can be conducted at different periods to ascertain any similarities or differences. This also allows any number of variables to be evaluated. For verification, studies on prevailing conditions can also be repeated to draw trends.

Advantages of descriptive research

Some of the significant advantages of descriptive research are:

• Data collection: A researcher can conduct descriptive research using specific methods like observational method, case study method, and survey method. Between these three, all primary data collection methods are covered, which provides a lot of information. This can be used for future research or even for developing a hypothesis for your research object.
• Varied: Since the data collected is qualitative and quantitative, it gives a holistic understanding of a research topic. The information is varied, diverse, and thorough.
• Natural environment: Descriptive research allows for the research to be conducted in the respondent’s natural environment, which ensures that high-quality and honest data is collected.
• Quick to perform and cheap: As the sample size is generally large in descriptive research, the data collection is quick to conduct and is inexpensive.

Descriptive research methods

There are three distinctive methods to conduct descriptive research. They are:

Observational method

The observational method is the most effective method to conduct this research, and researchers make use of both quantitative and qualitative observations.

A quantitative observation is the objective collection of data primarily focused on numbers and values. It suggests “associated with, of or depicted in terms of a quantity.” Results of quantitative observation are derived using statistical and numerical analysis methods. It implies observation of any entity associated with a numeric value such as age, shape, weight, volume, scale, etc. For example, the researcher can track if current customers will refer the brand using a simple Net Promoter Score question .

Qualitative observation doesn’t involve measurements or numbers but instead just monitoring characteristics. In this case, the researcher observes the respondents from a distance. Since the respondents are in a comfortable environment, the characteristics observed are natural and effective. In a descriptive research design, the researcher can choose to be either a complete observer, an observer as a participant, a participant as an observer, or a full participant. For example, in a supermarket, a researcher can from afar monitor and track the customers’ selection and purchasing trends. This offers a more in-depth insight into the purchasing experience of the customer.

Case study method

Case studies involve in-depth research and study of individuals or groups. Case studies lead to a hypothesis and widen a further scope of studying a phenomenon. However, case studies should not be used to determine cause and effect as they can’t make accurate predictions because there could be a bias on the researcher’s part. The other reason why case studies are not a reliable way of conducting descriptive research is that there could be an atypical respondent in the survey. Describing them leads to weak generalizations and moving away from external validity.

Survey research

In survey research, respondents answer through surveys or questionnaires or polls . They are a popular market research tool to collect feedback from respondents. A study to gather useful data should have the right survey questions. It should be a balanced mix of open-ended questions and close ended-questions . The survey method can be conducted online or offline, making it the go-to option for descriptive research where the sample size is enormous.

Examples of descriptive research

Some examples of descriptive research are:

• A specialty food group launching a new range of barbecue rubs would like to understand what flavors of rubs are favored by different people. To understand the preferred flavor palette, they conduct this type of research study using various methods like observational methods in supermarkets. By also surveying while collecting in-depth demographic information, offers insights about the preference of different markets. This can also help tailor make the rubs and spreads to various preferred meats in that demographic. Conducting this type of research helps the organization tweak their business model and amplify marketing in core markets.
• Another example of where this research can be used is if a school district wishes to evaluate teachers’ attitudes about using technology in the classroom. By conducting surveys and observing their comfortableness using technology through observational methods, the researcher can gauge what they can help understand if a full-fledged implementation can face an issue. This also helps in understanding if the students are impacted in any way with this change.

Some other research problems and research questions that can lead to descriptive research are:

• Market researchers want to observe the habits of consumers.
• A company wants to evaluate the morale of its staff.
• A school district wants to understand if students will access online lessons rather than textbooks.
• To understand if its wellness questionnaire programs enhance the overall health of the employees.

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• What is descriptive research?

Last updated

5 February 2023

Reviewed by

Cathy Heath

Short on time? Get an AI generated summary of this article instead

Descriptive research is a common investigatory model used by researchers in various fields, including social sciences, linguistics, and academia.

Read on to understand the characteristics of descriptive research and explore its underlying techniques, processes, and procedures.

Analyze your descriptive research

Dovetail streamlines analysis to help you uncover and share actionable insights

Descriptive research is an exploratory research method. It enables researchers to precisely and methodically describe a population, circumstance, or phenomenon.

As the name suggests, descriptive research describes the characteristics of the group, situation, or phenomenon being studied without manipulating variables or testing hypotheses . This can be reported using surveys , observational studies, and case studies. You can use both quantitative and qualitative methods to compile the data.

Besides making observations and then comparing and analyzing them, descriptive studies often develop knowledge concepts and provide solutions to critical issues. It always aims to answer how the event occurred, when it occurred, where it occurred, and what the problem or phenomenon is.

• Characteristics of descriptive research

The following are some of the characteristics of descriptive research:

Quantitativeness

Descriptive research can be quantitative as it gathers quantifiable data to statistically analyze a population sample. These numbers can show patterns, connections, and trends over time and can be discovered using surveys, polls, and experiments.

Qualitativeness

Descriptive research can also be qualitative. It gives meaning and context to the numbers supplied by quantitative descriptive research .

Researchers can use tools like interviews, focus groups, and ethnographic studies to illustrate why things are what they are and help characterize the research problem. This is because it’s more explanatory than exploratory or experimental research.

Uncontrolled variables

Descriptive research differs from experimental research in that researchers cannot manipulate the variables. They are recognized, scrutinized, and quantified instead. This is one of its most prominent features.

Cross-sectional studies

Descriptive research is a cross-sectional study because it examines several areas of the same group. It involves obtaining data on multiple variables at the personal level during a certain period. It’s helpful when trying to understand a larger community’s habits or preferences.

Carried out in a natural environment

Descriptive studies are usually carried out in the participants’ everyday environment, which allows researchers to avoid influencing responders by collecting data in a natural setting. You can use online surveys or survey questions to collect data or observe.

Basis for further research

You can further dissect descriptive research’s outcomes and use them for different types of investigation. The outcomes also serve as a foundation for subsequent investigations and can guide future studies. For example, you can use the data obtained in descriptive research to help determine future research designs.

• Descriptive research methods

There are three basic approaches for gathering data in descriptive research: observational, case study, and survey.

You can use surveys to gather data in descriptive research. This involves gathering information from many people using a questionnaire and interview .

Surveys remain the dominant research tool for descriptive research design. Researchers can conduct various investigations and collect multiple types of data (quantitative and qualitative) using surveys with diverse designs.

You can conduct surveys over the phone, online, or in person. Your survey might be a brief interview or conversation with a set of prepared questions intended to obtain quick information from the primary source.

Observation

This descriptive research method involves observing and gathering data on a population or phenomena without manipulating variables. It is employed in psychology, market research , and other social science studies to track and understand human behavior.

Observation is an essential component of descriptive research. It entails gathering data and analyzing it to see whether there is a relationship between the two variables in the study. This strategy usually allows for both qualitative and quantitative data analysis.

Case studies

A case study can outline a specific topic’s traits. The topic might be a person, group, event, or organization.

It involves using a subset of a larger group as a sample to characterize the features of that larger group.

You can generalize knowledge gained from studying a case study to benefit a broader audience.

This approach entails carefully examining a particular group, person, or event over time. You can learn something new about the study topic by using a small group to better understand the dynamics of the entire group.

• Types of descriptive research

There are several types of descriptive study. The most well-known include cross-sectional studies, census surveys, sample surveys, case reports, and comparison studies.

Case reports and case series

In the healthcare and medical fields, a case report is used to explain a patient’s circumstances when suffering from an uncommon illness or displaying certain symptoms. Case reports and case series are both collections of related cases. They have aided the advancement of medical knowledge on countless occasions.

The normative component is an addition to the descriptive survey. In the descriptive–normative survey, you compare the study’s results to the norm.

Descriptive survey

This descriptive type of research employs surveys to collect information on various topics. This data aims to determine the degree to which certain conditions may be attained.

You can extrapolate or generalize the information you obtain from sample surveys to the larger group being researched.

Correlative survey

Correlative surveys help establish if there is a positive, negative, or neutral connection between two variables.

Performing census surveys involves gathering relevant data on several aspects of a given population. These units include individuals, families, organizations, objects, characteristics, and properties.

During descriptive research, you gather different degrees of interest over time from a specific population. Cross-sectional studies provide a glimpse of a phenomenon’s prevalence and features in a population. There are no ethical challenges with them and they are quite simple and inexpensive to carry out.

Comparative studies

These surveys compare the two subjects’ conditions or characteristics. The subjects may include research variables, organizations, plans, and people.

Comparison points, assumption of similarities, and criteria of comparison are three important variables that affect how well and accurately comparative studies are conducted.

For instance, descriptive research can help determine how many CEOs hold a bachelor’s degree and what proportion of low-income households receive government help.

• Pros and cons

The primary advantage of descriptive research designs is that researchers can create a reliable and beneficial database for additional study. To conduct any inquiry, you need access to reliable information sources that can give you a firm understanding of a situation.

Quantitative studies are time- and resource-intensive, so knowing the hypotheses viable for testing is crucial. The basic overview of descriptive research provides helpful hints as to which variables are worth quantitatively examining. This is why it’s employed as a precursor to quantitative research designs.

Some experts view this research as untrustworthy and unscientific. However, there is no way to assess the findings because you don’t manipulate any variables statistically.

Cause-and-effect correlations also can’t be established through descriptive investigations. Additionally, observational study findings cannot be replicated, which prevents a review of the findings and their replication.

The absence of statistical and in-depth analysis and the rather superficial character of the investigative procedure are drawbacks of this research approach.

• Descriptive research examples and applications

Several descriptive research examples are emphasized based on their types, purposes, and applications. Research questions often begin with “What is …” These studies help find solutions to practical issues in social science, physical science, and education.

Here are some examples and applications of descriptive research:

Determining consumer perception and behavior

Organizations use descriptive research designs to determine how various demographic groups react to a certain product or service.

For example, a business looking to sell to its target market should research the market’s behavior first. When researching human behavior in response to a cause or event, the researcher pays attention to the traits, actions, and responses before drawing a conclusion.

Scientific classification

Scientific descriptive research enables the classification of organisms and their traits and constituents.

Measuring data trends

A descriptive study design’s statistical capabilities allow researchers to track data trends over time. It’s frequently used to determine the study target’s current circumstances and underlying patterns.

Conduct comparison

Organizations can use a descriptive research approach to learn how various demographics react to a certain product or service. For example, you can study how the target market responds to a competitor’s product and use that information to infer their behavior.

• Bottom line

A descriptive research design is suitable for exploring certain topics and serving as a prelude to larger quantitative investigations. It provides a comprehensive understanding of the “what” of the group or thing you’re investigating.

This research type acts as the cornerstone of other research methodologies . It is distinctive because it can use quantitative and qualitative research approaches at the same time.

What is descriptive research design?

Descriptive research design aims to systematically obtain information to describe a phenomenon, situation, or population. More specifically, it helps answer the what, when, where, and how questions regarding the research problem rather than the why.

How does descriptive research compare to qualitative research?

Despite certain parallels, descriptive research concentrates on describing phenomena, while qualitative research aims to understand people better.

How do you analyze descriptive research data?

Data analysis involves using various methodologies, enabling the researcher to evaluate and provide results regarding validity and reliability.

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Descriptive Research 101: Definition, Methods and Examples

Parvathi Vijayamohan

Last Updated: 16 July 2024

10 min read

Table Of Contents

• Descriptive Research 101: The Definitive Guide

What is Descriptive Research?

• Key Characteristics
• Observation
• Case Studies
• Types of Descriptive Research
• Question Examples
• Real-World Examples

Tips to Excel at Descriptive Research

• More Interesting Reads

Imagine you are a detective called to a crime scene. Your job is to study the scene and report whatever you find: whether that’s the half-smoked cigarette on the table or the large “RACHE” written in blood on the wall. That, in a nutshell, is  descriptive research .

Researchers often need to do descriptive research on a problem before they attempt to solve it. So in this guide, we’ll take you through:

• What is descriptive research + its characteristics
• Descriptive research methods
• Types of descriptive research
• Descriptive research examples
• Tips to excel at the descriptive method

Click to jump to the section that interests you.

Let’s begin by going through what descriptive studies can and cannot do.

Definition: As its name says, descriptive research  describes  the characteristics of the problem, phenomenon, situation, or group under study.

So the goal of all descriptive studies is to  explore  the background, details, and existing patterns in the problem to fully understand it. In other words, preliminary research.

However, descriptive research can be both  preliminary and conclusive . You can use the data from a descriptive study to make reports and get insights for further planning.

What descriptive research isn’t: Descriptive research finds the  what/when/where  of a problem, not the  why/how .

Because of this, we can’t use the descriptive method to explore cause-and-effect relationships where one variable (like a person’s job role) affects another variable (like their monthly income).

Key Characteristics of Descriptive Research

• Answers the “what,” “when,” and “where”  of a research problem. For this reason, it is popularly used in  market research ,  awareness surveys , and  opinion polls .
• Sets the stage  for a research problem. As an early part of the research process, descriptive studies help you dive deeper into the topic.
• Opens the door  for further research. You can use descriptive data as the basis for more profound research, analysis and studies.
• Qualitative and quantitative research . It is possible to get a balanced mix of numerical responses and open-ended answers from the descriptive method.
• No control or interference with the variables . The researcher simply observes and reports on them. However, specific research software has filters that allow her to zoom in on one variable.
• Done in natural settings . You can get the best results from descriptive research by talking to people, surveying them, or observing them in a suitable environment. For example, suppose you are a website beta testing an app feature. In that case, descriptive research invites users to try the feature, tracking their behavior and then asking their opinions .
• Can be applied to many research methods and areas. Examples include healthcare, SaaS, psychology, political studies, education, and pop culture.

Descriptive Research Methods: The Top Three You Need to Know!

In short, survey research is a brief interview or conversation with a set of prepared questions about a topic. So you create a questionnaire, share it, and analyze the data you collect for further action.

Read more : The difference between surveys vs questionnaires

• Surveys can be hyper-local, regional, or global, depending on your objectives.
• Share surveys in-person, offline, via SMS, email, or QR codes – so many options!
• Easy to automate if you want to conduct many surveys over a period.

FYI: If you’re looking for the perfect tool to conduct descriptive research, SurveySparrow’s got you covered. Our AI-powered text and sentiment analysis help you instantly capture detailed insights for your studies.

With 1,000+ customizable (and free) survey templates , 20+ question types, and 1500+ integrations , SurveySparrow makes research super-easy.

Want to try out our platform? Click on the template below to start using it.👇

Product Market Research Survey Template

Preview Template

2. Observation

The observational method is a type of descriptive research in which you, the researcher, observe ongoing behavior.

Now, there are several (non-creepy) ways you can observe someone. In fact, observational research has three main approaches:

• Covert observation: In true spy fashion, the researcher mixes in with the group undetected or observes from a distance.
• Overt observation : The researcher identifies himself as a researcher – “The name’s Bond. J. Bond.” – and explains the purpose of the study.
• Participatory observation : The researcher participates in what he is observing to understand his topic better.
• Observation is one of the most accurate ways to get data on a subject’s behavior in a natural setting.
• You don’t need to rely on people’s willingness to share information.
• Observation is a universal method that can be applied to any area of research.

3. Case Studies

In the case study method, you do a detailed study of a specific group, person, or event over a period.

This brings us to a frequently asked question: “What’s the difference between case studies and longitudinal studies?”

A case study will go  very in-depth into the subject with one-on-one interviews, observations, and archival research. They are also qualitative, though sometimes they will use numbers and stats.

An example of longitudinal research would be a study of the health of night shift employees vs. general shift employees over a decade. An example of a case study would involve in-depth interviews with Casey, an assistant director of nursing who’s handled the night shift at the hospital for ten years now.

• Due to the focus on a few people, case studies can give you a tremendous amount of information.
• Because of the time and effort involved, a case study engages both researchers and participants.
• Case studies are helpful for ethically investigating unusual, complex, or challenging subjects. An example would be a study of the habits of long-term cocaine users.

7 Types of Descriptive Research

Descriptive Research Question Examples

• How have teen social media habits changed in 10 years?
• What causes high employee turnover in tech?
• How do urban and rural diets differ in India?
• What are consumer preferences for electric vs. gasoline cars in Germany?
• How common is smartphone addiction among UK college students?
• What drives customer satisfaction in banking?
• How have adolescent mental health issues changed in 15 years?
• What leisure activities are popular among retirees in Japan?
• How do commute times vary in US metro areas?
• What makes e-commerce websites successful?

Descriptive Research: Real-World Examples To Build Your Next Study

1. case study: airbnb’s growth strategy.

In an excellent case study, Tam Al Saad, Principal Consultant, Strategy + Growth at Webprofits, deep dives into how Airbnb attracted and retained 150 million users .

“What Airbnb offers isn’t a cheap place to sleep when you’re on holiday; it’s the opportunity to experience your destination as a local would. It’s the chance to meet the locals, experience the markets, and find non-touristy places.

Sure, you can visit the Louvre, see Buckingham Palace, and climb the Empire State Building, but you can do it as if it were your hometown while staying in a place that has character and feels like a home.” – Tam al Saad, Principal Consultant, Strategy + Growth at Webprofits

2. Observation – Better Tech Experiences for the Elderly

We often think that our elders are so hopeless with technology. But we’re not getting any younger either, and tech is changing at a hair trigger! This article by Annemieke Hendricks shares a wonderful example where researchers compare the levels of technological familiarity between age groups and how that influences usage.

“It is generally assumed that older adults have difficulty using modern electronic devices, such as mobile telephones or computers. Because this age group is growing in most countries, changing products and processes to adapt to their needs is increasingly more important. “ – Annemieke Hendricks, Marketing Communication Specialist, Noldus

3. Surveys – Decoding Sleep with SurveySparrow

SRI International (formerly Stanford Research Institute) – an independent, non-profit research center – wanted to investigate the impact of stress on an adolescent’s sleep. To get those insights, two actions were essential: tracking sleep patterns through wearable devices and sending surveys at a pre-set time – the pre-sleep period.

“With SurveySparrow’s recurring surveys feature, SRI was able to share engaging surveys with their participants exactly at the time they wanted and at the frequency they preferred.”

Read more about this project : How SRI International decoded sleep patterns with SurveySparrow

1: Answer the six Ws –

• Who should we consider?
• What information do we need?
• When should we collect the information?
• Where should we collect the information?
• Why are we obtaining the information?
• Way to collect the information

#2: Introduce and explain your methodological approach

#3: Describe your methods of data collection and/or selection.

#4: Describe your methods of analysis.

#5: Explain the reasoning behind your choices.

#6: Collect data.

#7: Analyze the data. Use software to speed up the process and reduce overthinking and human error.

#8: Report your conclusions and how you drew the results.

Wrapping Up

Whether it’s social media habits, consumer preferences, or mental health trends, descriptive research provides a clear snapshot into what people actually think.

If you want to know more about feedback methodology, or research, check out some of our other articles below.

👉 Desk Research 101: Definition, Methods, and Examples

👉 Exploratory Research: Your Guide to Unraveling Insights

👉 Design Research: Types, Methods, and Importance

Content marketer at SurveySparrow.

Parvathi is a sociologist turned marketer. After 6 years as a copywriter, she pivoted to B2B, diving into growth marketing for SaaS. Now she uses content and conversion optimization to fuel growth - focusing on CX, reputation management and feedback methodology for businesses.

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Bridging the Gap: Overcome these 7 flaws in descriptive research design

Descriptive research design is a powerful tool used by scientists and researchers to gather information about a particular group or phenomenon. This type of research provides a detailed and accurate picture of the characteristics and behaviors of a particular population or subject. By observing and collecting data on a given topic, descriptive research helps researchers gain a deeper understanding of a specific issue and provides valuable insights that can inform future studies.

In this blog, we will explore the definition, characteristics, and common flaws in descriptive research design, and provide tips on how to avoid these pitfalls to produce high-quality results. Whether you are a seasoned researcher or a student just starting, understanding the fundamentals of descriptive research design is essential to conducting successful scientific studies.

Table of Contents

What Is Descriptive Research Design?

The descriptive research design involves observing and collecting data on a given topic without attempting to infer cause-and-effect relationships. The goal of descriptive research is to provide a comprehensive and accurate picture of the population or phenomenon being studied and to describe the relationships, patterns, and trends that exist within the data.

Descriptive research methods can include surveys, observational studies , and case studies, and the data collected can be qualitative or quantitative . The findings from descriptive research provide valuable insights and inform future research, but do not establish cause-and-effect relationships.

Importance of Descriptive Research in Scientific Studies

1. understanding of a population or phenomenon.

Descriptive research provides a comprehensive picture of the characteristics and behaviors of a particular population or phenomenon, allowing researchers to gain a deeper understanding of the topic.

2. Baseline Information

The information gathered through descriptive research can serve as a baseline for future research and provide a foundation for further studies.

3. Informative Data

Descriptive research can provide valuable information and insights into a particular topic, which can inform future research, policy decisions, and programs.

4. Sampling Validation

Descriptive research can be used to validate sampling methods and to help researchers determine the best approach for their study.

5. Cost Effective

Descriptive research is often less expensive and less time-consuming than other research methods , making it a cost-effective way to gather information about a particular population or phenomenon.

6. Easy to Replicate

Descriptive research is straightforward to replicate, making it a reliable way to gather and compare information from multiple sources.

Key Characteristics of Descriptive Research Design

The primary purpose of descriptive research is to describe the characteristics, behaviors, and attributes of a particular population or phenomenon.

2. Participants and Sampling

Descriptive research studies a particular population or sample that is representative of the larger population being studied. Furthermore, sampling methods can include convenience, stratified, or random sampling.

3. Data Collection Techniques

Descriptive research typically involves the collection of both qualitative and quantitative data through methods such as surveys, observational studies, case studies, or focus groups.

4. Data Analysis

Descriptive research data is analyzed to identify patterns, relationships, and trends within the data. Statistical techniques , such as frequency distributions and descriptive statistics, are commonly used to summarize and describe the data.

5. Focus on Description

Descriptive research is focused on describing and summarizing the characteristics of a particular population or phenomenon. It does not make causal inferences.

6. Non-Experimental

Descriptive research is non-experimental, meaning that the researcher does not manipulate variables or control conditions. The researcher simply observes and collects data on the population or phenomenon being studied.

When Can a Researcher Conduct Descriptive Research?

A researcher can conduct descriptive research in the following situations:

• To better understand a particular population or phenomenon
• To describe the relationships between variables
• To describe patterns and trends
• To validate sampling methods and determine the best approach for a study
• To compare data from multiple sources.

Types of Descriptive Research Design

1. survey research.

Surveys are a type of descriptive research that involves collecting data through self-administered or interviewer-administered questionnaires. Additionally, they can be administered in-person, by mail, or online, and can collect both qualitative and quantitative data.

2. Observational Research

Observational research involves observing and collecting data on a particular population or phenomenon without manipulating variables or controlling conditions. It can be conducted in naturalistic settings or controlled laboratory settings.

3. Case Study Research

Case study research is a type of descriptive research that focuses on a single individual, group, or event. It involves collecting detailed information on the subject through a variety of methods, including interviews, observations, and examination of documents.

4. Focus Group Research

Focus group research involves bringing together a small group of people to discuss a particular topic or product. Furthermore, the group is usually moderated by a researcher and the discussion is recorded for later analysis.

5. Ethnographic Research

Ethnographic research involves conducting detailed observations of a particular culture or community. It is often used to gain a deep understanding of the beliefs, behaviors, and practices of a particular group.

Advantages of Descriptive Research Design

1. provides a comprehensive understanding.

Descriptive research provides a comprehensive picture of the characteristics, behaviors, and attributes of a particular population or phenomenon, which can be useful in informing future research and policy decisions.

2. Non-invasive

Descriptive research is non-invasive and does not manipulate variables or control conditions, making it a suitable method for sensitive or ethical concerns.

3. Flexibility

Descriptive research allows for a wide range of data collection methods , including surveys, observational studies, case studies, and focus groups, making it a flexible and versatile research method.

4. Cost-effective

Descriptive research is often less expensive and less time-consuming than other research methods. Moreover, it gives a cost-effective option to many researchers.

5. Easy to Replicate

Descriptive research is easy to replicate, making it a reliable way to gather and compare information from multiple sources.

6. Informs Future Research

The insights gained from a descriptive research can inform future research and inform policy decisions and programs.

Disadvantages of Descriptive Research Design

1. limited scope.

Descriptive research only provides a snapshot of the current situation and cannot establish cause-and-effect relationships.

2. Dependence on Existing Data

Descriptive research relies on existing data, which may not always be comprehensive or accurate.

3. Lack of Control

Researchers have no control over the variables in descriptive research, which can limit the conclusions that can be drawn.

The researcher’s own biases and preconceptions can influence the interpretation of the data.

5. Lack of Generalizability

Descriptive research findings may not be applicable to other populations or situations.

6. Lack of Depth

Descriptive research provides a surface-level understanding of a phenomenon, rather than a deep understanding.

7. Time-consuming

Descriptive research often requires a large amount of data collection and analysis, which can be time-consuming and resource-intensive.

7 Ways to Avoid Common Flaws While Designing Descriptive Research

1. Clearly define the research question

A clearly defined research question is the foundation of any research study, and it is important to ensure that the question is both specific and relevant to the topic being studied.

2. Choose the appropriate research design

Choosing the appropriate research design for a study is crucial to the success of the study. Moreover, researchers should choose a design that best fits the research question and the type of data needed to answer it.

3. Select a representative sample

Selecting a representative sample is important to ensure that the findings of the study are generalizable to the population being studied. Researchers should use a sampling method that provides a random and representative sample of the population.

4. Use valid and reliable data collection methods

Using valid and reliable data collection methods is important to ensure that the data collected is accurate and can be used to answer the research question. Researchers should choose methods that are appropriate for the study and that can be administered consistently and systematically.

5. Minimize bias

Bias can significantly impact the validity and reliability of research findings.  Furthermore, it is important to minimize bias in all aspects of the study, from the selection of participants to the analysis of data.

6. Ensure adequate sample size

An adequate sample size is important to ensure that the results of the study are statistically significant and can be generalized to the population being studied.

7. Use appropriate data analysis techniques

The appropriate data analysis technique depends on the type of data collected and the research question being asked. Researchers should choose techniques that are appropriate for the data and the question being asked.

Have you worked on descriptive research designs? How was your experience creating a descriptive design? What challenges did you face? Do write to us or leave a comment below and share your insights on descriptive research designs!

extremely very educative

Indeed very educative and useful. Well explained. Thank you

Simple,easy to understand

Excellent and easy to understand queries and questions get answered easily. Its rather clear than any confusion. Thanks a million Shritika Sirisilla.

Easy to understand. Well written , educative and informative

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Descriptive Research

Descriptive research can be explained as a statement of affairs as they are at present with the researcher having no control over variable. Moreover, “descriptive studies may be characterised as simply the attempt to determine, describe or identify what is, while analytical research attempts to establish why it is that way or how it came to be” [1] . Three main purposes of descriptive studies can be explained as describing, explaining and validating research findings. This type of research is popular with non-quantified topic.

Descriptive research is “aimed at casting light on current issues or problems through a process of data collection that enables them to describe the situation more completely than was possible without employing this method.” [2] To put it simply, descriptive studies are used to describe various aspects of the phenomenon. In its popular format, descriptive research is used to describe characteristics and/or behaviour of sample population. It is an effective method to get information that can be used to develop hypotheses and propose associations.

Importantly, these types of studies do not focus on reasons for the occurrence of the phenomenon. In other words, descriptive research focuses on the question “What?”, but it is not concerned with the question “Why?”

Descriptive studies have the following characteristics:

1. While descriptive research can employ a number of variables, only one variable is required to conduct a descriptive study.

2. Descriptive studies are closely associated with observational studies, but they are not limited with observation data collection method. Case studies and  surveys can also be specified as popular data collection methods used with descriptive studies.

3. Findings of descriptive researches create a scope for further research. When a descriptive study answers to the question “What?”, a further research can be conducted to find an answer to “Why?” question.

Examples of Descriptive Research

Research questions in descriptive studies typically start with ‘What is…”. Examples of research questions in descriptive studies may include the following:

• What are the most effective intangible employee motivation tools in hospitality industry in the 21 st century?
• What is the impact of viral marketing on consumer behaviour in consumer amongst university students in Canada?
• Do corporate leaders of multinational companies in the 21 st century possess moral rights to receive multi-million bonuses?
• What are the main distinctive traits of organisational culture of McDonald’s USA?
• What is the impact of the global financial crisis of 2007 – 2009 on fitness industry in the UK?

Advantages of Descriptive Research

• Effective to analyse non-quantified topics and issues
• The possibility to observe the phenomenon in a completely natural and unchanged natural environment
• The opportunity to integrate the qualitative and quantitative methods of data collection. Accordingly, research findings can be comprehensive.
• Less time-consuming than quantitative experiments
• Practical use of research findings for decision-making

Disadvantages of Descriptive Research

• Descriptive studies cannot test or verify the research problem statistically
• Research results may reflect certain level of bias due to the absence of statistical tests
• The majority of descriptive studies are not ‘repeatable’ due to their observational nature
• Descriptive studies are not helpful in identifying cause behind described phenomenon

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  contains discussions of theory and application of research designs. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research approach ,  methods of data collection ,  data analysis  and  sampling  are explained in this e-book in simple words.

John Dudovskiy

[1] Ethridge, D.E. (2004) “Research Methodology in Applied Economics” John Wiley & Sons, p.24

[2] Fox, W. & Bayat, M.S. (2007) “A Guide to Managing Research” Juta Publications, p.45

41.1 What Is Descriptive Research? The type of question asked by the researcher will ultimately determine the type of approach necessary to complete an accurate assessment of the topic at hand. Descriptive studies, primarily concerned with finding out "what is," might be applied to investigate the following questions: Do teachers hold favorable attitudes toward using computers in schools? What kinds of activities that involve technology occur in sixth-grade classrooms and how frequently do they occur? What have been the reactions of school administrators to technological innovations in teaching the social sciences? How have high school computing courses changed over the last 10 years? How do the new multimediated textbooks compare to the print-based textbooks? How are decisions being made about using Channel One in schools, and for those schools that choose to use it, how is Channel One being implemented? What is the best way to provide access to computer equipment in schools? How should instructional designers improve software design to make the software more appealing to students? To what degree are special-education teachers well versed concerning assistive technology? Is there a relationship between experience with multimedia computers and problem-solving skills? How successful is a certain satellite-delivered Spanish course in terms of motivational value and academic achievement? Do teachers actually implement technology in the way they perceive? How many people use the AECT gopher server, and what do they use if for? Descriptive research can be either quantitative or qualitative. It can involve collections of quantitative information that can be tabulated along a continuum in numerical form, such as scores on a test or the number of times a person chooses to use a-certain feature of a multimedia program, or it can describe categories of information such as gender or patterns of interaction when using technology in a group situation. Descriptive research involves gathering data that describe events and then organizes, tabulates, depicts, and describes the data collection (Glass & Hopkins, 1984). It often uses visual aids such as graphs and charts to aid the reader in understanding the data distribution. Because the human mind cannot extract the full import of a large mass of raw data, descriptive statistics are very important in reducing the data to manageable form. When in-depth, narrative descriptions of small numbers of cases are involved, the research uses description as a tool to organize data into patterns that emerge during analysis. Those patterns aid the mind in comprehending a qualitative study and its implications. Most quantitative research falls into two areas: studies that describe events and studies aimed at discovering inferences or causal relationships. Descriptive studies are aimed at finding out "what is," so observational and survey methods are frequently used to collect descriptive data (Borg & Gall, 1989). Studies of this type might describe the current state of multimedia usage in schools or patterns of activity resulting from group work at the computer. An example of this is Cochenour, Hakes, and Neal's (1994) study of trends in compressed video applications with education and the private sector. Descriptive studies report summary data such as measures of central tendency including the mean, median, mode, deviance from the mean, variation, percentage, and correlation between variables. Survey research commonly includes that type of measurement, but often goes beyond the descriptive statistics in order to draw inferences. See, for example, Signer's (1991) survey of computer-assisted instruction and at-risk students, or Nolan, McKinnon, and Soler's (1992) research on achieving equitable access to school computers. Thick, rich descriptions of phenomena can also emerge from qualitative studies, case studies, observational studies, interviews, and portfolio assessments. Robinson's (1994) case study of a televised news program in classrooms and Lee's (1994) case study about identifying values concerning school restructuring are excellent examples of case studies. Descriptive research is unique in the number of variables employed. Like other types of research, descriptive research can include multiple variables for analysis, yet unlike other methods, it requires only one variable (Borg & Gall, 1989). For example, a descriptive study might employ methods of analyzing correlations between multiple variables by using tests such as Pearson's Product Moment correlation, regression, or multiple regression analysis. Good examples of this are the Knupfer and Hayes (1994) study about the effects of the Channel One broadcast on knowledge of current events, Manaev's (1991) study about mass media effectiveness, McKenna's (1993) study of the relationship between attributes of a radio program and it's appeal to listeners, Orey and Nelson's (1994) examination of learner interactions with hypermedia environments, and Shapiro's (1991) study of memory and decision processes. On the other hand, descriptive research might simply report the percentage summary on a single variable. Examples of this are the tally of reference citations in selected instructional design and technology journals by Anglin and Towers (1992); Barry's (1994) investigation of the controversy surrounding advertising and Channel One; Lu, Morlan, Lerchlorlarn, Lee, and Dike's (1993) investigation of the international utilization of media in education (1993); and Pettersson, Metallinos, Muffoletto, Shaw, and Takakuwa's (1993) analysis of the use of verbo-visual information in teaching geography in various countries. Descriptive statistics utilize data collection and analysis techniques that yield reports concerning the measures of central tendency, variation, and correlation. The combination of its characteristic summary and correlational statistics, along with its focus on specific types of research questions, methods, and outcomes is what distinguishes descriptive research from other research types. Three main purposes of research are to describe, explain, and validate findings. Description emerges following creative exploration, and serves to organize the findings in order to fit them with explanations, and then test or validate those explanations (Krathwohl, 1993). Many research studies call for the description of natural or man-made phenomena such as their form, structure, activity, change over time, relation to other phenomena, and so on. The description often illuminates knowledge that we might not otherwise notice or even encounter. Several important scientific discoveries as well as anthropological information about events outside of our common experiences have resulted from making such descriptions. For example, astronomers use their telescopes to develop descriptions of different parts of the universe, anthropologists describe life events of socially atypical situations or cultures uniquely different from our own, and educational researchers describe activities within classrooms concerning the implementation of technology. This process sometimes results in the discovery of stars and stellar events, new knowledge about value systems or practices of other cultures, or even the reality of classroom life as new technologies are implemented within schools. Educational researchers might use observational, survey, and interview techniques to collect data about group dynamics during computer-based activities. These data could then be used to recommend specific strategies for implementing computers or improving teaching strategies. Two excellent studies concerning the role of collaborative groups were conducted by Webb (1982), and Rysavy and Sales (1991). Noreen Webb's landmark study used descriptive research techniques to investigate collaborative groups as they worked within classrooms. Rysavy and Sales also apply a descriptive approach to study the role of group collaboration for working at computers. The Rysavy and Sales approach did not observe students in classrooms, but reported certain common findings that emerged through a literature search. Descriptive studies have an important role in educational research. They have greatly increased our knowledge about what happens in schools. Some of the important books in education have reported studies of this type: Life in Classrooms, by Philip Jackson; The Good High School, by Sara Lawrence Lightfoot; Teachers and Machines: The Classroom Use of Technology Since 1920, by Larry Cuban; A Place Called School, by John Goodlad; Visual Literacy: A Spectrum of Learning, by D. M. Moore and Dwyer; Computers in Education: Social, Political, and Historical Perspectives, by Muffoletto and Knupfer; and Contemporary Issues in American Distance Education, by M. G. Moore. Henry J. Becker's (1986) series of survey reports concerning the implementation of computers into schools across the United States as well as Nancy Nelson Knupfer's (1988) reports about teacher's opinions and patterns of computer usage also fit partially within the realm of descriptive research. Both studies describe categories of data and use statistical analysis to examine correlations between specific variables. Both also go beyond the bounds of descriptive research and conduct further statistical procedures appropriate to their research questions, thus enabling them to make further recommendations about implementing computing technology in ways to support grassroots change and equitable practices within the schools. Finally, Knupfer's study extended the analysis and conclusions in order to yield suggestions for instructional designers involved with educational computing. 41.1.1 The Nature of Descriptive Research The descriptive function of research is heavily dependent on instrumentation for measurement and observation (Borg & Gall, 1989). Researchers may work for many years to perfect such instrumentation so that the resulting measurement will be accurate, reliable, and generalizable. Instruments such as the electron microscope, standardized tests for various purposes, the United States census, Michael Simonson's questionnaires about computer usage, and scores of thoroughly validated questionnaires are examples of some instruments that yield valuable descriptive data. Once the instruments are developed, they can be used to describe phenomena of interest to the researchers. The intent of some descriptive research is to produce statistical information about aspects of education that interests policy makers and educators. The National Center for Education Statistics specializes in this kind of research. Many of its findings are published in an annual volume called Digest of Educational Statistics. The center also administers the National Assessment of Educational Progress (NAEP), which collects descriptive information about how well the nation's youth are doing in various subject areas. A typical NAEP publication is The Reading Report Card, which provides descriptive information about the reading achievement of junior high and high school students during the past 2 decades. On a larger scale, the International Association for the Evaluation of Education Achievement (IEA) has done major descriptive studies comparing the academic achievement levels of students in many different nations, including the United States (Borg & Gall, 1989). Within the United States, huge amounts of information are being gathered continuously by the Office of Technology Assessment, which influences policy concerning technology in education. As a way of offering guidance about the potential of technologies for distance education, that office has published a book called Linking for Learning: A New Course for Education, which offers descriptions of distance education and its potential. There has been an ongoing debate among researchers about the value of quantitative (see 40.1.2) versus qualitative research, and certain remarks have targeted descriptive research as being less pure than traditional experimental, quantitative designs. Rumors abound that young researchers must conduct quantitative research in order to get published in Educational Technology Research and Development and other prestigious journals in the field. One camp argues the benefits of a scientific approach to educational research, thus preferring the experimental, quantitative approach, while the other camp posits the need to recognize the unique human side of educational research questions and thus prefers to use qualitative research methodology. Because descriptive research spans both quantitative and qualitative methodologies, it brings the ability to describe events in greater or less depth as needed, to focus on various elements of different research techniques, and to engage quantitative statistics to organize information in meaningful ways. The citations within this chapter provide ample evidence that descriptive research can indeed be published in prestigious journals. Descriptive studies can yield rich data that lead to important recommendations. For example, Galloway (1992) bases recommendations for teaching with computer analogies on descriptive data, and Wehrs (1992) draws reasonable conclusions about using expert systems to support academic advising. On the other hand, descriptive research can be misused by those who do not understand its purpose and limitations. For example, one cannot try to draw conclusions that show cause and effect, because that is beyond the bounds of the statistics employed. Borg and Gall (1989) classify the outcomes of educational research into the four categories of description, prediction, improvement, and explanation. They say that descriptive research describes natural or man-made educational phenomena that is of interest to policy makers and educators. Predictions of educational phenomenon seek to determine whether certain students are at risk and if teachers should use different techniques to instruct them. Research about improvement asks whether a certain technique does something to help students learn better and whether certain interventions can improve student learning by applying causal-comparative, correlational, and experimental methods. The final category of explanation posits that research is able to explain a set of phenomena that leads to our ability to describe, predict, and control the phenomena with a high level of certainty and accuracy. This usually takes the form of theories. The methods of collecting data for descriptive research can be employed singly or in various combinations, depending on the research questions at hand. Descriptive research often calls upon quasi-experimental research design (Campbell & Stanley, 1963). Some of the common data collection methods applied to questions within the realm of descriptive research include surveys, interviews, observations, and portfolios. Updated Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices. Chapter 3. Psychological Science & Research 3.5 Psychologists Use Descriptive, Correlational, and Experimental Research Designs to Understand Behaviour Charles Stangor and Jennifer Walinga Learning Objectives Differentiate the goals of descriptive, correlational, and experimental research designs and explain the advantages and disadvantages of each. Explain the goals of descriptive research and the statistical techniques used to interpret it. Summarize the uses of correlational research and describe why correlational research cannot be used to infer causality. Review the procedures of experimental research and explain how it can be used to draw causal inferences. Psychologists agree that if their ideas and theories about human behaviour are to be taken seriously, they must be backed up by data. However, the research of different psychologists is designed with different goals in mind, and the different goals require different approaches. These varying approaches, summarized in Table 3.3, are known as research designs . A research design  is the specific method a researcher uses to collect, analyze, and interpret data . Psychologists use three major types of research designs in their research, and each provides an essential avenue for scientific investigation. Descriptive research  is research designed to provide a snapshot of the current state of affairs . Correlational research  is research designed to discover relationships among variables and to allow the prediction of future events from present knowledge . Experimental research  is research in which initial equivalence among research participants in more than one group is created, followed by a manipulation of a given experience for these groups and a measurement of the influence of the manipulation . Each of the three research designs varies according to its strengths and limitations, and it is important to understand how each differs. Research design Goal Advantages Disadvantages Descriptive To create a snapshot of the current state of affairs Provides a relatively complete picture of what is occurring at a given time. Allows the development of questions for further study. Does not assess relationships among variables. May be unethical if participants do not know they are being observed. Correlational To assess the relationships between and among two or more variables Allows testing of expected relationships between and among variables and the making of predictions. Can assess these relationships in everyday life events. Cannot be used to draw inferences about the causal relationships between and among the variables. Experimental To assess the causal impact of one or more experimental manipulations on a dependent variable Allows drawing of conclusions about the causal relationships among variables. Cannot experimentally manipulate many important variables. May be expensive and time consuming. Source: Stangor, 2011. Descriptive Research: Assessing the Current State of Affairs Descriptive research is designed to create a snapshot of the current thoughts, feelings, or behaviour of individuals. This section reviews three types of descriptive research : case studies , surveys , and naturalistic observation (Figure 3.3). Sometimes the data in a descriptive research project are based on only a small set of individuals, often only one person or a single small group. These research designs are known as case studies — descriptive records of one or more individual’s experiences and behaviour . Sometimes case studies involve ordinary individuals, as when developmental psychologist Jean Piaget used his observation of his own children to develop his stage theory of cognitive development. More frequently, case studies are conducted on individuals who have unusual or abnormal experiences or characteristics or who find themselves in particularly difficult or stressful situations. The assumption is that by carefully studying individuals who are socially marginal, who are experiencing unusual situations, or who are going through a difficult phase in their lives, we can learn something about human nature. Sigmund Freud was a master of using the psychological difficulties of individuals to draw conclusions about basic psychological processes. Freud wrote case studies of some of his most interesting patients and used these careful examinations to develop his important theories of personality. One classic example is Freud’s description of “Little Hans,” a child whose fear of horses the psychoanalyst interpreted in terms of repressed sexual impulses and the Oedipus complex (Freud, 1909/1964). Another well-known case study is Phineas Gage, a man whose thoughts and emotions were extensively studied by cognitive psychologists after a railroad spike was blasted through his skull in an accident. Although there are questions about the interpretation of this case study (Kotowicz, 2007), it did provide early evidence that the brain’s frontal lobe is involved in emotion and morality (Damasio et al., 2005). An interesting example of a case study in clinical psychology is described by Rokeach (1964), who investigated in detail the beliefs of and interactions among three patients with schizophrenia, all of whom were convinced they were Jesus Christ. In other cases the data from descriptive research projects come in the form of a survey — a measure administered through either an interview or a written questionnaire to get a picture of the beliefs or behaviours of a sample of people of interest . The people chosen to participate in the research (known as the sample) are selected to be representative of all the people that the researcher wishes to know about (the population). In election polls, for instance, a sample is taken from the population of all “likely voters” in the upcoming elections. The results of surveys may sometimes be rather mundane, such as “Nine out of 10 doctors prefer Tymenocin” or “The median income in the city of Hamilton is $46,712.” Yet other times (particularly in discussions of social behaviour), the results can be shocking: “More than 40,000 people are killed by gunfire in the United States every year” or “More than 60% of women between the ages of 50 and 60 suffer from depression.” Descriptive research is frequently used by psychologists to get an estimate of the prevalence (or incidence ) of psychological disorders. A final type of descriptive research — known as naturalistic observation — is research based on the observation of everyday events . For instance, a developmental psychologist who watches children on a playground and describes what they say to each other while they play is conducting descriptive research, as is a biopsychologist who observes animals in their natural habitats. One example of observational research involves a systematic procedure known as the strange situation , used to get a picture of how adults and young children interact. The data that are collected in the strange situation are systematically coded in a coding sheet such as that shown in Table 3.4. Coder name: This table represents a sample coding sheet from an episode of the “strange situation,” in which an infant (usually about one year old) is observed playing in a room with two adults — the child’s mother and a stranger. Each of the four coding categories is scored by the coder from 1 (the baby makes no effort to engage in the behaviour) to 7 (the baby makes a significant effort to engage in the behaviour). More information about the meaning of the coding can be found in Ainsworth, Blehar, Waters, and Wall (1978). Episode Coding categories Proximity Contact Resistance Avoidance Mother and baby play alone 1 1 1 1 Mother puts baby down 4 1 1 1 Stranger enters room 1 2 3 1 Mother leaves room; stranger plays with baby 1 3 1 1 Mother re-enters, greets and may comfort baby, then leaves again 4 2 1 2 Stranger tries to play with baby 1 3 1 1 Mother re-enters and picks up baby 6 6 1 2 Source: Stangor, 2011. The results of descriptive research projects are analyzed using descriptive statistics — numbers that summarize the distribution of scores on a measured variable . Most variables have distributions similar to that shown in Figure 3.4 where most of the scores are located near the centre of the distribution, and the distribution is symmetrical and bell-shaped. A data distribution that is shaped like a bell is known as a normal distribution . A distribution can be described in terms of its central tendency — that is, the point in the distribution around which the data are centred — and its dispersion, or spread . The arithmetic average, or arithmetic mean , symbolized by the letter M , is the most commonly used measure of central tendency . It is computed by calculating the sum of all the scores of the variable and dividing this sum by the number of participants in the distribution (denoted by the letter N ). In the data presented in Figure 3.4 the mean height of the students is 67.12 inches (170.5 cm). The sample mean is usually indicated by the letter M . In some cases, however, the data distribution is not symmetrical. This occurs when there are one or more extreme scores (known as outliers ) at one end of the distribution. Consider, for instance, the variable of family income (see Figure 3.6), which includes an outlier (a value of $3,800,000). In this case the mean is not a good measure of central tendency. Although it appears from Figure 3.5 that the central tendency of the family income variable should be around $70,000, the mean family income is actually $223,960. The single very extreme income has a disproportionate impact on the mean, resulting in a value that does not well represent the central tendency. The median is used as an alternative measure of central tendency when distributions are not symmetrical. The median  is the score in the center of the distribution, meaning that 50% of the scores are greater than the median and 50% of the scores are less than the median . In our case, the median household income ($73,000) is a much better indication of central tendency than is the mean household income ($223,960). A final measure of central tendency, known as the mode , represents the value that occurs most frequently in the distribution . You can see from Figure 3.5 that the mode for the family income variable is $93,000 (it occurs four times). In addition to summarizing the central tendency of a distribution, descriptive statistics convey information about how the scores of the variable are spread around the central tendency. Dispersion refers to the extent to which the scores are all tightly clustered around the central tendency , as seen in Figure 3.6. Or they may be more spread out away from it, as seen in Figure 3.7. One simple measure of dispersion is to find the largest (the maximum ) and the smallest (the minimum ) observed values of the variable and to compute the range of the variable as the maximum observed score minus the minimum observed score. You can check that the range of the height variable in Figure 3.4 is 72 – 62 = 10. The standard deviation , symbolized as s , is the most commonly used measure of dispersion . Distributions with a larger standard deviation have more spread. The standard deviation of the height variable is s = 2.74, and the standard deviation of the family income variable is s = $745,337. An advantage of descriptive research is that it attempts to capture the complexity of everyday behaviour. Case studies provide detailed information about a single person or a small group of people, surveys capture the thoughts or reported behaviours of a large population of people, and naturalistic observation objectively records the behaviour of people or animals as it occurs naturally. Thus descriptive research is used to provide a relatively complete understanding of what is currently happening. Despite these advantages, descriptive research has a distinct disadvantage in that, although it allows us to get an idea of what is currently happening, it is usually limited to static pictures. Although descriptions of particular experiences may be interesting, they are not always transferable to other individuals in other situations, nor do they tell us exactly why specific behaviours or events occurred. For instance, descriptions of individuals who have suffered a stressful event, such as a war or an earthquake, can be used to understand the individuals’ reactions to the event but cannot tell us anything about the long-term effects of the stress. And because there is no comparison group that did not experience the stressful situation, we cannot know what these individuals would be like if they hadn’t had the stressful experience. Correlational Research: Seeking Relationships among Variables In contrast to descriptive research, which is designed primarily to provide static pictures, correlational research involves the measurement of two or more relevant variables and an assessment of the relationship between or among those variables. For instance, the variables of height and weight are systematically related (correlated) because taller people generally weigh more than shorter people. In the same way, study time and memory errors are also related, because the more time a person is given to study a list of words, the fewer errors he or she will make. When there are two variables in the research design, one of them is called the predictor variable and the other the outcome variable . The research design can be visualized as shown in Figure 3.8, where the curved arrow represents the expected correlation between these two variables. One way of organizing the data from a correlational study with two variables is to graph the values of each of the measured variables using a scatter plot . As you can see in Figure 3.9 a scatter plot  is a visual image of the relationship between two variables . A point is plotted for each individual at the intersection of his or her scores for the two variables. When the association between the variables on the scatter plot can be easily approximated with a straight line , as in parts (a) and (b) of Figure 3.9 the variables are said to have a linear relationship . When the straight line indicates that individuals who have above-average values for one variable also tend to have above-average values for the other variable , as in part (a), the relationship is said to be positive linear . Examples of positive linear relationships include those between height and weight, between education and income, and between age and mathematical abilities in children. In each case, people who score higher on one of the variables also tend to score higher on the other variable. Negative linear relationships , in contrast, as shown in part (b), occur when above-average values for one variable tend to be associated with below-average values for the other variable. Examples of negative linear relationships include those between the age of a child and the number of diapers the child uses, and between practice on and errors made on a learning task. In these cases, people who score higher on one of the variables tend to score lower on the other variable. Relationships between variables that cannot be described with a straight line are known as nonlinear relationships . Part (c) of Figure 3.9 shows a common pattern in which the distribution of the points is essentially random. In this case there is no relationship at all between the two variables , and they are said to be independent . Parts (d) and (e) of Figure 3.9 show patterns of association in which, although there is an association, the points are not well described by a single straight line. For instance, part (d) shows the type of relationship that frequently occurs between anxiety and performance. Increases in anxiety from low to moderate levels are associated with performance increases, whereas increases in anxiety from moderate to high levels are associated with decreases in performance. Relationships that change in direction and thus are not described by a single straight line are called curvilinear relationships . The most common statistical measure of the strength of linear relationships among variables is the Pearson correlation coefficient , which is symbolized by the letter r . The value of the correlation coefficient ranges from r = –1.00 to r = +1.00. The direction of the linear relationship is indicated by the sign of the correlation coefficient. Positive values of r (such as r = .54 or r = .67) indicate that the relationship is positive linear (i.e., the pattern of the dots on the scatter plot runs from the lower left to the upper right), whereas negative values of r (such as r = –.30 or r = –.72) indicate negative linear relationships (i.e., the dots run from the upper left to the lower right). The strength of the linear relationship is indexed by the distance of the correlation coefficient from zero (its absolute value). For instance, r = –.54 is a stronger relationship than r = .30, and r = .72 is a stronger relationship than r = –.57. Because the Pearson correlation coefficient only measures linear relationships, variables that have curvilinear relationships are not well described by r , and the observed correlation will be close to zero. It is also possible to study relationships among more than two measures at the same time. A research design in which more than one predictor variable is used to predict a single outcome variable is analyzed through multiple regression (Aiken & West, 1991).  Multiple regression  is a statistical technique, based on correlation coefficients among variables, that allows predicting a single outcome variable from more than one predictor variable . For instance, Figure 3.10 shows a multiple regression analysis in which three predictor variables (Salary, job satisfaction, and years employed) are used to predict a single outcome (job performance). The use of multiple regression analysis shows an important advantage of correlational research designs — they can be used to make predictions about a person’s likely score on an outcome variable (e.g., job performance) based on knowledge of other variables. An important limitation of correlational research designs is that they cannot be used to draw conclusions about the causal relationships among the measured variables. Consider, for instance, a researcher who has hypothesized that viewing violent behaviour will cause increased aggressive play in children. He has collected, from a sample of Grade 4 children, a measure of how many violent television shows each child views during the week, as well as a measure of how aggressively each child plays on the school playground. From his collected data, the researcher discovers a positive correlation between the two measured variables. Although this positive correlation appears to support the researcher’s hypothesis, it cannot be taken to indicate that viewing violent television causes aggressive behaviour. Although the researcher is tempted to assume that viewing violent television causes aggressive play, there are other possibilities. One alternative possibility is that the causal direction is exactly opposite from what has been hypothesized. Perhaps children who have behaved aggressively at school develop residual excitement that leads them to want to watch violent television shows at home (Figure 3.12): Although this possibility may seem less likely, there is no way to rule out the possibility of such reverse causation on the basis of this observed correlation. It is also possible that both causal directions are operating and that the two variables cause each other (Figure 3.13). Still another possible explanation for the observed correlation is that it has been produced by the presence of a common-causal variable (also known as a third variable ). A common-causal variable  is a variable that is not part of the research hypothesis but that causes both the predictor and the outcome variable and thus produces the observed correlation between them . In our example, a potential common-causal variable is the discipline style of the children’s parents. Parents who use a harsh and punitive discipline style may produce children who like to watch violent television and who also behave aggressively in comparison to children whose parents use less harsh discipline (Figure 3.14) In this case, television viewing and aggressive play would be positively correlated (as indicated by the curved arrow between them), even though neither one caused the other but they were both caused by the discipline style of the parents (the straight arrows). When the predictor and outcome variables are both caused by a common-causal variable, the observed relationship between them is said to be spurious . A spurious relationship  is a relationship between two variables in which a common-causal variable produces and “explains away” the relationship . If effects of the common-causal variable were taken away, or controlled for, the relationship between the predictor and outcome variables would disappear. In the example, the relationship between aggression and television viewing might be spurious because by controlling for the effect of the parents’ disciplining style, the relationship between television viewing and aggressive behaviour might go away. Common-causal variables in correlational research designs can be thought of as mystery variables because, as they have not been measured, their presence and identity are usually unknown to the researcher. Since it is not possible to measure every variable that could cause both the predictor and outcome variables, the existence of an unknown common-causal variable is always a possibility. For this reason, we are left with the basic limitation of correlational research: correlation does not demonstrate causation. It is important that when you read about correlational research projects, you keep in mind the possibility of spurious relationships, and be sure to interpret the findings appropriately. Although correlational research is sometimes reported as demonstrating causality without any mention being made of the possibility of reverse causation or common-causal variables, informed consumers of research, like you, are aware of these interpretational problems. In sum, correlational research designs have both strengths and limitations. One strength is that they can be used when experimental research is not possible because the predictor variables cannot be manipulated. Correlational designs also have the advantage of allowing the researcher to study behaviour as it occurs in everyday life. And we can also use correlational designs to make predictions — for instance, to predict from the scores on their battery of tests the success of job trainees during a training session. But we cannot use such correlational information to determine whether the training caused better job performance. For that, researchers rely on experiments. Experimental Research: Understanding the Causes of Behaviour The goal of experimental research design is to provide more definitive conclusions about the causal relationships among the variables in the research hypothesis than is available from correlational designs. In an experimental research design, the variables of interest are called the independent variable (or variables ) and the dependent variable . The independent variable  in an experiment is the causing variable that is created (manipulated) by the experimenter . The dependent variable  in an experiment is a measured variable that is expected to be influenced by the experimental manipulation . The research hypothesis suggests that the manipulated independent variable or variables will cause changes in the measured dependent variables. We can diagram the research hypothesis by using an arrow that points in one direction. This demonstrates the expected direction of causality (Figure 3.15): Research Focus: Video Games and Aggression Consider an experiment conducted by Anderson and Dill (2000). The study was designed to test the hypothesis that viewing violent video games would increase aggressive behaviour. In this research, male and female undergraduates from Iowa State University were given a chance to play with either a violent video game (Wolfenstein 3D) or a nonviolent video game (Myst). During the experimental session, the participants played their assigned video games for 15 minutes. Then, after the play, each participant played a competitive game with an opponent in which the participant could deliver blasts of white noise through the earphones of the opponent. The operational definition of the dependent variable (aggressive behaviour) was the level and duration of noise delivered to the opponent. The design of the experiment is shown in Figure 3.16 Two advantages of the experimental research design are (a) the assurance that the independent variable (also known as the experimental manipulation ) occurs prior to the measured dependent variable, and (b) the creation of initial equivalence between the conditions of the experiment (in this case by using random assignment to conditions). Experimental designs have two very nice features. For one, they guarantee that the independent variable occurs prior to the measurement of the dependent variable. This eliminates the possibility of reverse causation. Second, the influence of common-causal variables is controlled, and thus eliminated, by creating initial equivalence among the participants in each of the experimental conditions before the manipulation occurs. The most common method of creating equivalence among the experimental conditions is through random assignment to conditions, a procedure in which the condition that each participant is assigned to is determined through a random process, such as drawing numbers out of an envelope or using a random number table . Anderson and Dill first randomly assigned about 100 participants to each of their two groups (Group A and Group B). Because they used random assignment to conditions, they could be confident that, before the experimental manipulation occurred, the students in Group A were, on average, equivalent to the students in Group B on every possible variable, including variables that are likely to be related to aggression, such as parental discipline style, peer relationships, hormone levels, diet — and in fact everything else. Then, after they had created initial equivalence, Anderson and Dill created the experimental manipulation — they had the participants in Group A play the violent game and the participants in Group B play the nonviolent game. Then they compared the dependent variable (the white noise blasts) between the two groups, finding that the students who had viewed the violent video game gave significantly longer noise blasts than did the students who had played the nonviolent game. Anderson and Dill had from the outset created initial equivalence between the groups. This initial equivalence allowed them to observe differences in the white noise levels between the two groups after the experimental manipulation, leading to the conclusion that it was the independent variable (and not some other variable) that caused these differences. The idea is that the only thing that was different between the students in the two groups was the video game they had played. Despite the advantage of determining causation, experiments do have limitations. One is that they are often conducted in laboratory situations rather than in the everyday lives of people. Therefore, we do not know whether results that we find in a laboratory setting will necessarily hold up in everyday life. Second, and more important, is that some of the most interesting and key social variables cannot be experimentally manipulated. If we want to study the influence of the size of a mob on the destructiveness of its behaviour, or to compare the personality characteristics of people who join suicide cults with those of people who do not join such cults, these relationships must be assessed using correlational designs, because it is simply not possible to experimentally manipulate these variables. Key Takeaways Descriptive, correlational, and experimental research designs are used to collect and analyze data. Descriptive designs include case studies, surveys, and naturalistic observation. The goal of these designs is to get a picture of the current thoughts, feelings, or behaviours in a given group of people. Descriptive research is summarized using descriptive statistics. Correlational research designs measure two or more relevant variables and assess a relationship between or among them. The variables may be presented on a scatter plot to visually show the relationships. The Pearson Correlation Coefficient ( r ) is a measure of the strength of linear relationship between two variables. Common-causal variables may cause both the predictor and outcome variable in a correlational design, producing a spurious relationship. The possibility of common-causal variables makes it impossible to draw causal conclusions from correlational research designs. Experimental research involves the manipulation of an independent variable and the measurement of a dependent variable. Random assignment to conditions is normally used to create initial equivalence between the groups, allowing researchers to draw causal conclusions. Exercises and Critical Thinking There is a negative correlation between the row that a student sits in in a large class (when the rows are numbered from front to back) and his or her final grade in the class. Do you think this represents a causal relationship or a spurious relationship, and why? Think of two variables (other than those mentioned in this book) that are likely to be correlated, but in which the correlation is probably spurious. What is the likely common-causal variable that is producing the relationship? Imagine a researcher wants to test the hypothesis that participating in psychotherapy will cause a decrease in reported anxiety. Describe the type of research design the investigator might use to draw this conclusion. What would be the independent and dependent variables in the research? Image Attributions Figure 3.3: “ Reading newspaper ” by Alaskan Dude (http://commons.wikimedia.org/wiki/File:Reading_newspaper.jpg) is licensed under CC BY 2.0 Aiken, L., & West, S. (1991).  Multiple regression: Testing and interpreting interactions . Newbury Park, CA: Sage. Ainsworth, M. S., Blehar, M. C., Waters, E., & Wall, S. (1978).  Patterns of attachment: A psychological study of the strange situation . Hillsdale, NJ: Lawrence Erlbaum Associates. Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life.  Journal of Personality and Social Psychology, 78 (4), 772–790. Damasio, H., Grabowski, T., Frank, R., Galaburda, A. M., Damasio, A. R., Cacioppo, J. T., & Berntson, G. G. (2005). The return of Phineas Gage: Clues about the brain from the skull of a famous patient. In  Social neuroscience: Key readings.  (pp. 21–28). New York, NY: Psychology Press. Freud, S. (1909/1964). Analysis of phobia in a five-year-old boy. In E. A. Southwell & M. Merbaum (Eds.),  Personality: Readings in theory and research  (pp. 3–32). Belmont, CA: Wadsworth. (Original work published 1909). Kotowicz, Z. (2007). The strange case of Phineas Gage.  History of the Human Sciences, 20 (1), 115–131. Rokeach, M. (1964).  The three Christs of Ypsilanti: A psychological study . New York, NY: Knopf. Stangor, C. (2011). Research methods for the behavioural sciences (4th ed.). Mountain View, CA: Cengage. Long Descriptions Figure 3.5 long description: There are 25 families. 24 families have an income between $44,000 and $111,000 and one family has an income of $3,800,000. The mean income is $223,960 while the median income is $73,000. Figure 3.9 long description: Types of scatter plots. Positive linear, r=positive .82. The plots on the graph form a rough line that runs from lower left to upper right. Negative linear, r=negative .70. The plots on the graph form a rough line that runs from upper left to lower right. Independent, r=0.00. The plots on the graph are spread out around the centre. Curvilinear, r=0.00. The plots of the graph form a rough line that goes up and then down like a hill. Curvilinear, r=0.00. The plots on the graph for a rough line that goes down and then up like a ditch. Introduction to Psychology Copyright © 2019 by Charles Stangor and Jennifer Walinga is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted. Share This Book What Is Descriptive Research? Jan 29, 2020 There are many methods of marketing research that traverse a variety of industries. We’ve already talked about  ethnographic research  and how it compares to marketing research methods. Descriptive research, while somewhat similar, is different in that specific marketing research methods actually fall under it. Descriptive research is a methodology that is not exclusive to market researchers but one that can apply to a variety of research methods used in healthcare, psychology, and education. At its core, descriptive research seeks to describe the characteristics or behavior of an audience. While it’s not grounded in statistics, and usually leans towards more qualitative methods, it can include quantifiable data as well. The purpose of descriptive research is, of course, to describe, as well as explain, or validate some sort of hypothesis or objective when it comes to a specific group of people. There are three main methods of descriptive research: Observation:  There are two methods of observation including in-field and lab observation. In-field observation requires viewing or recording of an audience in their natural environment. Lab observation, on the other hand, is driven by the scientific method and audiences undergo observation in a more controlled test environment. Case Studies:  Case studies involve a more in-depth analysis of an individual or smaller audience. Surveys:  Likely the most familiar method of descriptive research, surveys involve interviews or discussions with larger audiences and are often conducted on more specific topics. Each of these three methods of descriptive research serves its own purpose. However, we find that leveraging a unique combination of surveys and discussions is often the most effective in meeting many marketing objectives. Leveraging Descriptive Research Methods Too often surveys depart from the primary objectives of descriptive research. For example, a need for quantifiable data and validation can detract from descriptive objectives and the need to understand an audience first. However, focus groups and our exploratory research design supplement this departure. Specifically, exploratory research is meant to do exactly what descriptive research hopes to achieve but in a more manageable way. Through online discussions, researchers can interpret conversations that describe, evaluate, or document behaviors. Respondents are able to portray everything from attitudes and feelings to processes, reactions, relationships, and more. When taking advantage of any research method, there are always considerations to keep in mind. In the case of descriptive research, there are two specific types of bias to avoid in order to remain objective and avoid errors in insights: Ecological Fallacy:  Drawing conclusions about an individual based on the analysis of a larger group. Exception Fallacy:  The opposite of ecological fallacy, this is drawing conclusions about a group of people based on one individual—similar to stereotyping. Targeting the appropriate audience will help avoid this bias. The right respondents who find the topic of research relatable and applicable to their daily lives will also help garner more detailed discussions. To learn more about how we incorporate both qualitative and quantitative methods of descriptive research, download the  eGuide below. You’ll also learn the differences and benefits of combining the two methodologies. Want to stay up to date latest GutCheck blog posts? Follow us on, check out our most recent blog posts. When Vocation and Avocation Collide Jun 13, 2023 At GutCheck, we have four brand pillars upon which we build our business. One of those is to 'lead... Reflections on Season 1 of Gutsiest Brands Jun 1, 2023 Understanding people is at the heart of market research. Sure, companies want to know what ideas... Permission to Evolve with Miguel Garcia Castillo Apr 20, 2023 (highlights from Episode #22 of the Gutsiest Brands podcast) Check out the latest lessons from our... Why GutCheck? Explore and Strategize Build Products and Ideas Promote and Communicate Brand Measurement and Tracking Case Studies Infographics Research Reports Press Releases Gutsiest Brands 1-877-990-8111 [email protected] © 2023 GutCheck is a registered trademark of Brainyak, Inc. All rights reserved. Privacy Policy , Cookies , & Acceptable Use , Do Not Sell My Information © 2020 GutCheck is a registered trademark of Brainyak, Inc. All rights reserved. Privacy Policy , Cookies , & Acceptable Use 493 IMAGES PPT Descriptive research: definition, types and examples descriptive Descriptive Research: Methods, Types, and Examples PPT Descriptive Research: Methods, Types, and Examples Descriptive Research: Characteristics, Methods + Examples COMMENTS Descriptive Research Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what, where, when and how questions, but not why questions. A descriptive research design can use a wide variety of research methods to investigate one or more variables. Unlike in experimental research, the researcher does ... (PDF) Descriptive Research Designs A descriptive correlation study was a research method that observes and characterizes the behavior of participants from a scientific standpoint in relation to factors in a setting. It seeks to ... Understanding Descriptive Research Designs and Methods According to Siedlecki (2020), the descriptive research design is a deliberate study that carefully and methodically explains, observes, or confirms group elements obtained through quantifiable ... Study designs: Part 2 INTRODUCTION. In our previous article in this series, [ 1] we introduced the concept of "study designs"- as "the set of methods and procedures used to collect and analyze data on variables specified in a particular research question.". Study designs are primarily of two types - observational and interventional, with the former being ... What is Descriptive Research? Definition, Methods, Types and Examples Descriptive research is a methodological approach that seeks to depict the characteristics of a phenomenon or subject under investigation. In scientific inquiry, it serves as a foundational tool for researchers aiming to observe, record, and analyze the intricate details of a particular topic. This method provides a rich and detailed account ... Characteristics of Qualitative Descriptive Studies: A Systematic Review Qualitative description (QD) is a term that is widely used to describe qualitative studies of health care and nursing-related phenomena. However, limited discussions regarding QD are found in the existing literature. In this systematic review, we identified characteristics of methods and findings reported in research articles published in 2014 ... Understanding Descriptive Research Designs and Methods Understanding Descriptive Research Designs and Methods. ... :8-12. doi: 10.1097/NUR.0000000000000493. Author Sandra L Siedlecki 1 Affiliation 1 Author Affiliation: Senior Nurse Scientist and Clinical Nurse Specialist, Office of Nursing Research & Innovation, Nursing Institute, Cleveland Clinic, Ohio. PMID ... Descriptive Research Design Definition: Descriptive research design is a type of research methodology that aims to describe or document the characteristics, behaviors, attitudes, opinions, or perceptions of a group or population being studied. Descriptive research design does not attempt to establish cause-and-effect relationships between variables or make predictions ... Descriptive Research Design Descriptive research aims to accurately and systematically describe a population, situation or phenomenon. It can answer what, where, when, and how questions, but not why questions. A descriptive research design can use a wide variety of research methods to investigate one or more variables. Unlike in experimental research, the researcher does ... Survey Descriptive Research: Design & Examples Here's a general definition that captures the essence of a descriptive survey research design definition by authors: A descriptive survey research design is a systematic and structured approach to collecting data from a sample of individuals or entities within a larger population, with the primary aim of providing a detailed and accurate ... Descriptive Research and Qualitative Research Descriptive research is a study of status and is widely used in education, nutrition, epidemiology, and the behavioral sciences. Its value is based on the premise that problems can be solved and practices improved through observation, analysis, and description. The most common descriptive research method is the survey, which includes ... Descriptive Research: Characteristics, Methods + Examples Descriptive research is a research method describing the characteristics of the population or phenomenon studied. This descriptive methodologyfocuses more on the "what" of the research subject than the "why" of the research subject. The method primarily focuses on describing the nature of a demographic segment without focusing on "why ... Descriptive Research: Design, Methods, Examples, and FAQs Descriptive research is an exploratory research method.It enables researchers to precisely and methodically describe a population, circumstance, or phenomenon.. As the name suggests, descriptive research describes the characteristics of the group, situation, or phenomenon being studied without manipulating variables or testing hypotheses.This can be reported using surveys, observational ... Descriptive Research 101: Definition, Methods and Examples Definition: As its name says, descriptive research describes the characteristics of the problem, phenomenon, situation, or group under study. So the goal of all descriptive studies is to explore the background, details, and existing patterns in the problem to fully understand it. In other words, preliminary research. Descriptive Research 1. Purpose. The primary purpose of descriptive research is to describe the characteristics, behaviors, and attributes of a particular population or phenomenon. 2. Participants and Sampling. Descriptive research studies a particular population or sample that is representative of the larger population being studied. Descriptive Research Descriptive studies have the following characteristics: 1. While descriptive research can employ a number of variables, only one variable is required to conduct a descriptive study. 2. Descriptive studies are closely associated with observational studies, but they are not limited with observation data collection method. An overview of the qualitative descriptive design within nursing research Inconsistency in decision making within the research process coupled with a lack of transparency has created issues of credibility for this type of approach. It can be difficult to clearly differentiate what constitutes a descriptive research design from the range of other methodologies at the disposal of qualitative researchers. PDF VOLUME 13 ISSUE 2.2 2018 2.1 Research Design This study made use of the descriptive research method because it dealt with the analysis of indirectness markers in the written discourse of the subjects under study. Calderon (2006), defined descriptive research as a purposive process of gathering, analyzing, classifying, and tabulating data about prevailing conditions, 41.1 What Is Descriptive Research? The term descriptive research refers to the type of research question, design, and data analysis that will be applied to a given topic. Descriptive statistics tell what is, while inferential statistics try to determine cause and effect. The type of question asked by the researcher will ultimately determine the type of approach necessary to ... 3.5 Psychologists Use Descriptive, Correlational, and Experimental A research design is the specific method a researcher uses to collect, analyze, and interpret data. Psychologists use three major types of research designs in their research, and each provides an essential avenue for scientific investigation. Descriptive research is research designed to provide a snapshot of the current state of affairs. (PDF) CHAPTER FIVE RESEARCH DESIGN AND METHODOLOGY 5.1. Introduction In other words, the research design sets the procedure on the required data, the methods to be applied to collect and analyze this data, and how all of this is going to answer the research ... What Is Descriptive Research? 3 Methods. Descriptive research is a methodology that is not exclusive to market researchers but one that can apply to a variety of research methods used in healthcare, psychology, and education. At its core, descriptive research seeks to describe the characteristics or behavior of an audience. While it's not grounded in statistics, and ... A Descriptive-Correlational Study of the Teachers' Motivation Specifically, it employed a descriptive-correlational research design to evaluate secondary teachers' writing motivation, research skills, and competence, and perspectives on the parts, scope, and ... assignment business plan case study course work essay report research paper speech term paper thesis