qualitative research and quantitative research examples

Qualitative vs Quantitative Research Methods & Data Analysis

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

• Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
• Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.

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What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography .

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective , exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context : Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise : Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity : Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias : The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity : Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis : Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication : Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Mixed methods research
• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

The 10 Key Differences Between Qualitative and Quantitative Research Methods

Sep 5, 2023 | Research FAQs

Understanding the Distinctions Between Qualitative and Quantitative Research Methods

In the realm of academic exploration and enquiry, research methods serve as the foundation upon which new knowledge is built. Among the multitude of methodologies available to researchers, two primary approaches stand out: qualitative and quantitative research methods. These distinct paradigms guide scholars in their quest for understanding, yet they diverge significantly in their techniques, purposes, and outcomes. In this short guide, we delve into the intricacies of qualitative and quantitative research methods, shedding light on their defining characteristics, applications, advantages, and limitations.

#1 The Essence of Qualitative and Quantitative Research

Qualitative research encompasses an in-depth exploration of the subjective aspects of a phenomenon, often employing methods such as interviews, focus groups, and content analysis. In contrast, quantitative research employs numerical data and statistical analyses to quantify relationships, relying on surveys, experiments, and secondary data analysis.

Qualitative research serves as a gateway to delving deeply into the intricacies of human experiences and behaviours. This approach involves immersing oneself in the subjective aspects of a phenomenon, allowing researchers to uncover hidden nuances that quantitative methods might overlook.

By employing methods such as in-depth interviews, focus groups, and content analysis, qualitative researchers venture into the rich tapestry of individual perspectives, motivations, and emotions. These methods provide a canvas upon which the complex interplay of human thought and emotion can be carefully unravelled.

On the other hand, quantitative research takes a step back to capture the broader picture through numbers and measurable relationships. This method is particularly suited for researchers seeking to quantify patterns, trends, and correlations that are prevalent across a larger population.

By employing numerical data and statistical analyses, such as surveys, experiments, and secondary data analysis, quantitative research unveils the statistical underpinnings that shape our world. This approach enables researchers to make generalisations and predictions based on empirical evidence, offering insights that transcend individual experiences.

#2 Philosophical Underpinnings

Qualitative research leans on interpretivism, emphasising the significance of context and multiple realities. It seeks to understand the social construction of reality and values subjective experiences. Quantitative research aligns with positivism, striving for objectivity and universal truths through observable and measurable phenomena.

In the philosophical realm, qualitative research embraces interpretivism, a perspective that acknowledges the role of context, culture, and individual perspectives in shaping reality. This approach recognises that reality is not an absolute, objective construct, but rather a fluid and dynamic interplay of various viewpoints. By diving into the subjective experiences of participants, qualitative research seeks to grasp the layers of meaning and significance that contribute to the complexity of human existence.

On the opposite end, quantitative research aligns with positivism, a perspective that seeks to uncover universal truths through systematic observation and measurement. Positivism operates under the premise that the world is governed by laws that can be objectively studied and measured. By focusing on observable and measurable phenomena, quantitative research strives to achieve objectivity and reliability. This alignment with positivism allows researchers to create a standardised framework for understanding reality, facilitating the comparison of findings across different studies and contexts.

#3 Data Collection Techniques

Qualitative research employs flexible, open-ended data collection techniques that allow researchers to explore unexpected avenues. These methods provide rich insights into complex social phenomena but may lack generalisability. Quantitative research relies on structured data collection, often through standardised surveys, ensuring replicable results and enabling statistical comparisons.

The heart of qualitative research lies in its adaptable and flexible data collection techniques. These methods are designed to accommodate the dynamic and unpredictable nature of human experiences. Qualitative researchers often engage in open-ended interviews, allowing participants to express themselves freely and reveal insights that might have remained concealed within closed-ended survey questions. Additionally, techniques such as focus groups and content analysis provide avenues for exploring collective perspectives and themes that emerge organically.

In the realm of quantitative research, structured data collection takes centre stage. Standardised surveys, carefully designed to measure specific variables, ensure consistency and comparability among responses. This approach allows researchers to collect a vast amount of data efficiently and quantitatively analyse patterns and trends. However, the structured nature of quantitative data collection may inadvertently limit the scope of responses, potentially overlooking nuances that qualitative methods excel at capturing.

#4 Sample Selection and Size

Qualitative research often employs purposive sampling to select participants with specific characteristics, ensuring a deep understanding of their experiences. In contrast, quantitative research emphasises random or stratified sampling to achieve representative samples, enhancing the potential for generalisability.

Qualitative research takes a targeted approach to sample selection through purposive sampling. By deliberately selecting participants who possess specific characteristics or experiences, researchers ensure a deep and comprehensive understanding of the phenomenon under investigation. 

This strategy is particularly beneficial when exploring complex, niche topics, as it enables researchers to capture the depth and diversity of perspectives within a smaller sample.

Conversely, quantitative research emphasises the importance of representative samples achieved through random or stratified sampling. This approach is rooted in the desire to generalise findings to a larger population. By selecting participants at random or based on specific criteria, quantitative researchers aim to minimise bias and increase the likelihood that their results are applicable beyond the study’s immediate context. This enables researchers to draw broader conclusions that transcend the boundaries of the sample studied.

#5 Analysis Process

Qualitative data analysis involves coding and thematic analysis to identify patterns and themes within textual or visual data. This approach requires researchers to immerse themselves in the data, fostering a nuanced understanding of the subject. Quantitative data analysis employs statistical techniques to analyse numerical data, allowing researchers to identify correlations, trends, and significant differences.

Qualitative data analysis is an art that requires researchers to immerse themselves in the data, navigating the intricate web of narratives, themes, and emotions. Through techniques such as coding and thematic analysis, researchers identify recurring patterns, extract meaningful insights, and construct a coherent narrative that captures the essence of participants’ experiences. This approach demands patience, creativity, and a willingness to let the data guide the analysis process.

In the realm of quantitative analysis, numbers take centre stage. Statistical techniques allow researchers to explore relationships, test hypotheses, and identify patterns within numerical data. From correlation coefficients to regression analyses, these tools enable researchers to uncover the statistical significance of their findings and make data-driven interpretations. Unlike qualitative analysis, quantitative analysis relies on predefined variables and measurements, guiding researchers toward predetermined outcomes.

#6 Validity and Reliability

Qualitative research focuses on ensuring validity through techniques such as triangulation, member checking, and prolonged engagement. While reliability in the traditional sense may be harder to achieve due to the subjective nature of the data, qualitative research prioritises credibility and transferability. Quantitative research emphasises reliability and internal validity, striving to minimise bias and produce consistent results.

Qualitative research prioritises validity through a multi-faceted approach that seeks to ensure the accuracy and credibility of findings. 

Techniques such as triangulation, which involves using multiple sources of data to confirm patterns, enhance the trustworthiness of qualitative results. Member checking, where participants review and validate the researcher’s interpretations, adds another layer of credibility. While achieving traditional reliability in the quantitative sense can be challenging due to the dynamic nature of qualitative data, qualitative research places a premium on establishing transferability and credibility.

Quantitative research, on the other hand, emphasises reliability and internal validity. Researchers employing quantitative methods seek to minimise the potential for bias and error by using standardised procedures and measures. This ensures that the study’s findings can be replicated consistently, contributing to the overall body of knowledge. Statistical techniques are often used to assess the reliability of measurements, and the careful design of experiments and surveys aims to control extraneous variables that could impact the internal validity of the study.

#7 Real-World Applications

Qualitative research is well-suited for exploring complex social phenomena, such as understanding the lived experiences of marginalised communities or analysing the intricacies of interpersonal relationships. Quantitative research finds its strength in empirical studies that require measurement and statistical analysis, such as clinical trials, market research, and opinion polls.

Qualitative research finds its stride in exploring the depths of complex social phenomena that cannot be easily quantified. It is ideally suited for gaining insights into the lived experiences of marginalised communities, understanding the nuances of cultural practices, or unravelling the intricacies of interpersonal relationships. Qualitative research provides a platform for amplifying voices that might otherwise remain unheard and uncovers the underlying emotional landscapes that shape human behaviour.

On the other hand, quantitative research’s strengths lie in empirical studies that demand numerical data and objective measurement. It thrives in scenarios where statistical analyses are essential for drawing conclusions. For instance, in clinical trials, quantitative research enables researchers to assess the effectiveness of treatments by analysing measurable outcomes. In market research, it quantifies consumer preferences and behaviours, guiding businesses in making data-driven decisions. In political opinion polls, quantitative research captures the pulse of public sentiment through quantifiable data.

#8 Complementary Roles

In certain cases, qualitative and quantitative research methods can complement each other, offering a more comprehensive view of a phenomenon. For instance, a mixed-methods approach could involve conducting qualitative interviews to gain insights and then designing a quantitative survey to validate findings on a larger scale.

The boundary between qualitative and quantitative research is not rigid; instead, they can be seen as complementary puzzle pieces. In some cases, combining these methods through a mixed-methods approach can offer a more holistic understanding of a phenomenon.

Imagine a study aiming to explore a social issue. Qualitative interviews might unveil the underlying narratives and emotions surrounding the issue, while a subsequent quantitative survey could provide statistical evidence to validate the qualitative findings on a larger scale. This harmonious combination bridges the gap between depth and breadth, offering a comprehensive perspective.

#9 Ethical Considerations

Qualitative research places strong emphasis on ethical considerations due to its potential for revealing sensitive personal experiences. Researchers must ensure informed consent, confidentiality, and emotional well-being of participants. In quantitative research, ethical considerations often revolve around issues of privacy and data protection, particularly in the era of big data.

In the realm of qualitative research, ethical considerations are paramount due to the potential for revealing personal, sensitive experiences

Researchers must navigate the delicate balance between seeking knowledge and ensuring the well-being of participants. Informed consent becomes crucial, as participants need to understand the purpose and potential outcomes of the study before they share their experiences. Confidentiality and anonymity are essential to protect participants’ identities and privacy. Researchers must also be mindful of the potential emotional impact on participants and offer resources for support.

In quantitative research, ethical considerations often revolve around issues of privacy, data protection, and informed consent in the era of big data. With vast amounts of digital information available, researchers must ensure that participants’ data is anonymised and secured to prevent unauthorised access. The challenge lies in balancing the need for data-driven insights with the responsibility of safeguarding individuals’ information. Researchers are called upon to uphold ethical standards while harnessing the power of quantitative methods.

#10 Evolving Landscape

The landscape of research methods is not static. Qualitative and quantitative research approaches continue to evolve as researchers explore innovative techniques. For instance, advancements in technology have led to the emergence of digital qualitative research methodologies, while big data analytics have expanded the horizons of quantitative research.

The landscape of research methods is far from static; it is continually evolving as researchers innovate and adapt to new challenges. Qualitative and quantitative research approaches are no exception. Technological advancements have given rise to digital qualitative research methodologies, allowing researchers to explore online communities and virtual spaces. The integration of multimedia, such as videos and images, has expanded the horizons of qualitative data analysis, enabling researchers to capture and analyse multi-modal forms of communication.

Similarly, the quantitative realm has been reshaped by the explosion of big data. With unprecedented access to massive datasets, researchers can explore patterns and trends that were previously beyond reach. Big data analytics have given rise to novel insights in fields such as healthcare, finance, and social sciences. Machine learning and artificial intelligence are transforming the way quantitative research is conducted, enabling researchers to make predictions and uncover hidden patterns with remarkable accuracy.

Key Takeaways

• Qualitative research delves into subjective experiences, while quantitative research focuses on numerical data and statistical analysis.
• Qualitative methods emphasise context and multiple realities, while quantitative methods strive for objectivity and universal truths.
• Qualitative research employs open-ended data collection and inductive analysis, while quantitative research relies on structured data collection and deductive analysis.
• Qualitative research seeks rich insights from small, purposive samples, while quantitative research aims for generalisability through representative samples.
• Both paradigms prioritise validity and reliability, but their definitions and techniques differ.
• Qualitative research excels in exploring complex social phenomena, while quantitative research shines in empirical studies and statistical analyses.
• A mixed-methods approach combines qualitative and quantitative research methods for a comprehensive understanding of a subject.

 In the dynamic world of academic research, the choice between qualitative and quantitative research methods is pivotal. The philosophical underpinnings, data collection techniques, analysis processes, and ethical considerations of each paradigm significantly influence the outcomes and applications of a study. As you embark on your research journey, consider the intricacies and strengths of each approach, allowing your research question to guide you toward the method best suited to uncovering the insights you seek.

As you delve deeper into the world of research, remember that these methodologies are not rigid categories but rather dynamic tools that can be adapted and blended to suit the needs of your study. The distinction between qualitative and quantitative research is not about one being superior to the other, but rather about recognising their distinct purposes and leveraging their unique strengths to contribute to the body of knowledge in your field.

Useful Resources

• Way With Words – Professional academic research transcription services.
• American Educational Research Association – A resource hub for educational research methodologies.
• Qualitative Research in Psychology – A journal exploring innovative qualitative research approaches.
• Quantitative Research Methods – An in-depth guide to various quantitative research methods.
• SAGE Research Methods – A comprehensive platform providing access to various research methods and resources.

Engagement Questions

• How might your research question influence your choice between qualitative and quantitative methods?
• Can you think of scenarios where combining qualitative and quantitative methods would enhance the validity of your study?
• In what ways do ethical considerations differ between qualitative and quantitative research, and how would you address them in your own study?