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Difference Between Qualitative and Quantitative Research

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Published: Mar 14, 2019

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Introduction, compare and contrast: qualitative and quantitative research, works cited.

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Sage Publications.
Denzin, N. K., & Lincoln, Y. S. (Eds.). (2018). The SAGE handbook of qualitative research (5th ed.). Sage Publications.
Neuman, W. L. (2014). Social research methods: Qualitative and quantitative approaches (7th ed.). Pearson.
Palys, T., & Atchison, C. (2018). Qualitative research in the digital era: Obstacles and opportunities. International Journal of Qualitative Methods, 17(1), 1-11. https://doi.org/10.1177/1609406918813901
Maxwell, J. A. (2013). Qualitative research design: An interactive approach (3rd ed.). Sage Publications.
Bryman, A. (2016). Social research methods (5th ed.). Oxford University Press.
Onwuegbuzie, A. J., & Leech, N. L. (2007). A call for qualitative power analyses. Quality & Quantity, 41(1), 105-121. https://doi.org/10.1007/s11135-006-9018-6
Babbie, E. (2016). The practice of social research (14th ed.). Cengage Learning.
Tashakkori, A., & Teddlie, C. (Eds.). (2019). SAGE handbook of mixed methods in social & behavioral research (3rd ed.). Sage Publications.
Morgan, D. L. (2013). Integrating qualitative and quantitative methods: A pragmatic approach. Sage Publications.

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Qualitative vs Quantitative Research Methods & Data Analysis

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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.

On This Page:

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

Educational resources and simple solutions for your research journey

Qualitative vs Quantitative Research: Differences, Examples, and Methods

There are two broad kinds of research approaches: qualitative and quantitative research that are used to study and analyze phenomena in various fields such as natural sciences, social sciences, and humanities. Whether you have realized it or not, your research must have followed either or both research types. In this article we will discuss what qualitative vs quantitative research is, their applications, pros and cons, and when to use qualitative vs quantitative research . Before we get into the details, it is important to understand the differences between the qualitative and quantitative research.

Table of Contents

Qualitative v s Quantitative Research

Quantitative research deals with quantity, hence, this research type is concerned with numbers and statistics to prove or disapprove theories or hypothesis. In contrast, qualitative research is all about quality – characteristics, unquantifiable features, and meanings to seek deeper understanding of behavior and phenomenon. These two methodologies serve complementary roles in the research process, each offering unique insights and methods suited to different research questions and objectives.

Qualitative and quantitative research approaches have their own unique characteristics, drawbacks, advantages, and uses. Where quantitative research is mostly employed to validate theories or assumptions with the goal of generalizing facts to the larger population, qualitative research is used to study concepts, thoughts, or experiences for the purpose of gaining the underlying reasons, motivations, and meanings behind human behavior .

What Are the Differences Between Qualitative and Quantitative Research

Qualitative and quantitative research differs in terms of the methods they employ to conduct, collect, and analyze data. For example, qualitative research usually relies on interviews, observations, and textual analysis to explore subjective experiences and diverse perspectives. While quantitative data collection methods include surveys, experiments, and statistical analysis to gather and analyze numerical data. The differences between the two research approaches across various aspects are listed in the table below.

Data Collection Methods

There are differences between qualitative and quantitative research when it comes to data collection as they deal with different types of data. Qualitative research is concerned with personal or descriptive accounts to understand human behavior within society. Quantitative research deals with numerical or measurable data to delineate relations among variables. Hence, the qualitative data collection methods differ significantly from quantitative data collection methods due to the nature of data being collected and the research objectives. Below is the list of data collection methods for each research approach:

Qualitative Research Data Collection

Interviews
Focus g roups
Content a nalysis
Literature review
Observation
Ethnography

Qualitative research data collection can involve one-on-one group interviews to capture in-depth perspectives of participants using open-ended questions. These interviews could be structured, semi-structured or unstructured depending upon the nature of the study. Focus groups can be used to explore specific topics and generate rich data through discussions among participants. Another qualitative data collection method is content analysis, which involves systematically analyzing text documents, audio, and video files or visual content to uncover patterns, themes, and meanings. This can be done through coding and categorization of raw data to draw meaningful insights. Data can be collected through observation studies where the goal is to simply observe and document behaviors, interaction, and phenomena in natural settings without interference. Lastly, ethnography allows one to immerse themselves in the culture or environment under study for a prolonged period to gain a deep understanding of the social phenomena.

Quantitative Research Data Collection

Surveys/ q uestionnaires
Experiments
Secondary data analysis
Structured o bservations
Case studies
Tests and a ssessments

Quantitative research data collection approaches comprise of fundamental methods for generating numerical data that can be analyzed using statistical or mathematical tools. The most common quantitative data collection approach is the usage of structured surveys with close-ended questions to collect quantifiable data from a large sample of participants. These can be conducted online, over the phone, or in person.

Performing experiments is another important data collection approach, in which variables are manipulated under controlled conditions to observe their effects on dependent variables. This often involves random assignment of participants to different conditions or groups. Such experimental settings are employed to gauge cause-and-effect relationships and understand a complex phenomenon. At times, instead of acquiring original data, researchers may deal with secondary data, which is the dataset curated by others, such as government agencies, research organizations, or academic institute. With structured observations, subjects in a natural environment can be studied by controlling the variables which aids in understanding the relationship among various variables. The secondary data is then analyzed to identify patterns and relationships among variables. Observational studies provide a means to systematically observe and record behaviors or phenomena as they occur in controlled environments. Case studies form an interesting study methodology in which a researcher studies a single entity or a small number of entities (individuals or organizations) in detail to understand complex phenomena within a specific context.

Qualitative vs Quantitative Research Outcomes

Qualitative research and quantitative research lead to varied research outcomes, each with its own strengths and limitations. For example, qualitative research outcomes provide deep descriptive accounts of human experiences, motivations, and perspectives that allow us to identify themes or narratives and context in which behavior, attitudes, or phenomena occurs. Quantitative research outcomes on the other hand produce numerical data that is analyzed statistically to establish patterns and relationships objectively, to form generalizations about the larger population and make predictions. This numerical data can be presented in the form of graphs, tables, or charts. Both approaches offer valuable perspectives on complex phenomena, with qualitative research focusing on depth and interpretation, while quantitative research emphasizes numerical analysis and objectivity.

When to Use Qualitative vs Quantitative Research Approach

The decision to choose between qualitative and quantitative research depends on various factors, such as the research question, objectives, whether you are taking an inductive or deductive approach, available resources, practical considerations such as time and money, and the nature of the phenomenon under investigation. To simplify, quantitative research can be used if the aim of the research is to prove or test a hypothesis, while qualitative research should be used if the research question is more exploratory and an in-depth understanding of the concepts, behavior, or experiences is needed.

Qualitative research approach

Qualitative research approach is used under following scenarios:

To study complex phenomena: When the research requires understanding the depth, complexity, and context of a phenomenon.
Collecting participant perspectives: When the goal is to understand the why behind a certain behavior, and a need to capture subjective experiences and perceptions of participants.
Generating hypotheses or theories: When generating hypotheses, theories, or conceptual frameworks based on exploratory research.

Example: If you have a research question “What obstacles do expatriate students encounter when acquiring a new language in their host country?”

This research question can be addressed using the qualitative research approach by conducting in-depth interviews with 15-25 expatriate university students. Ask open-ended questions such as “What are the major challenges you face while attempting to learn the new language?”, “Do you find it difficult to learn the language as an adult?”, and “Do you feel practicing with a native friend or colleague helps the learning process”?

Based on the findings of these answers, a follow-up questionnaire can be planned to clarify things. Next step will be to transcribe all interviews using transcription software and identify themes and patterns.

Quantitative research approach

Quantitative research approach is used under following scenarios:

Testing hypotheses or proving theories: When aiming to test hypotheses, establish relationships, or examine cause-and-effect relationships.
Generalizability: When needing findings that can be generalized to broader populations using large, representative samples.
Statistical analysis: When requiring rigorous statistical analysis to quantify relationships, patterns, or trends in data.

Example : Considering the above example, you can conduct a survey of 200-300 expatriate university students and ask them specific questions such as: “On a scale of 1-10 how difficult is it to learn a new language?”

Next, statistical analysis can be performed on the responses to draw conclusions like, on an average expatriate students rated the difficulty of learning a language 6.5 on the scale of 10.

Mixed methods approach

In many cases, researchers may opt for a mixed methods approach , combining qualitative and quantitative methods to leverage the strengths of both approaches. Researchers may use qualitative data to explore phenomena in-depth and generate hypotheses, while quantitative data can be used to test these hypotheses and generalize findings to broader populations.

Example: Both qualitative and quantitative research methods can be used in combination to address the above research question. Through open-ended questions you can gain insights about different perspectives and experiences while quantitative research allows you to test that knowledge and prove/disprove your hypothesis.

How to Analyze Qualitative and Quantitative Data

When it comes to analyzing qualitative and quantitative data, the focus is on identifying patterns in the data to highlight the relationship between elements. The best research method for any given study should be chosen based on the study aim. A few methods to analyze qualitative and quantitative data are listed below.

Analyzing qualitative data

Qualitative data analysis is challenging as it is not expressed in numbers and consists majorly of texts, images, or videos. Hence, care must be taken while using any analytical approach. Some common approaches to analyze qualitative data include:

Organization: The first step is data (transcripts or notes) organization into different categories with similar concepts, themes, and patterns to find inter-relationships.
Coding: Data can be arranged in categories based on themes/concepts using coding.
Theme development: Utilize higher-level organization to group related codes into broader themes.
Interpretation: Explore the meaning behind different emerging themes to understand connections. Use different perspectives like culture, environment, and status to evaluate emerging themes.
Reporting: Present findings with quotes or excerpts to illustrate key themes.

Analyzing quantitative data

Quantitative data analysis is more direct compared to qualitative data as it primarily deals with numbers. Data can be evaluated using simple math or advanced statistics (descriptive or inferential). Some common approaches to analyze quantitative data include:

Processing raw data: Check missing values, outliers, or inconsistencies in raw data.
Descriptive statistics: Summarize data with means, standard deviations, or standard error using programs such as Excel, SPSS, or R language.
Exploratory data analysis: Usage of visuals to deduce patterns and trends.
Hypothesis testing: Apply statistical tests to find significance and test hypothesis (Student’s t-test or ANOVA).
Interpretation: Analyze results considering significance and practical implications.
Validation: Data validation through replication or literature review.
Reporting: Present findings by means of tables, figures, or graphs.

Benefits and limitations of qualitative vs quantitative research

There are significant differences between qualitative and quantitative research; we have listed the benefits and limitations of both methods below:

Benefits of qualitative research

Rich insights: As qualitative research often produces information-rich data, it aids in gaining in-depth insights into complex phenomena, allowing researchers to explore nuances and meanings of the topic of study.
Flexibility: One of the most important benefits of qualitative research is flexibility in acquiring and analyzing data that allows researchers to adapt to the context and explore more unconventional aspects.
Contextual understanding: With descriptive and comprehensive data, understanding the context in which behaviors or phenomena occur becomes accessible.
Capturing different perspectives: Qualitative research allows for capturing different participant perspectives with open-ended question formats that further enrich data.
Hypothesis/theory generation: Qualitative research is often the first step in generating theory/hypothesis, which leads to future investigation thereby contributing to the field of research.

Limitations of qualitative research

Subjectivity: It is difficult to have objective interpretation with qualitative research, as research findings might be influenced by the expertise of researchers. The risk of researcher bias or interpretations affects the reliability and validity of the results.
Limited generalizability: Due to the presence of small, non-representative samples, the qualitative data cannot be used to make generalizations to a broader population.
Cost and time intensive: Qualitative data collection can be time-consuming and resource-intensive, therefore, it requires strategic planning and commitment.
Complex analysis: Analyzing qualitative data needs specialized skills and techniques, hence, it’s challenging for researchers without sufficient training or experience.
Potential misinterpretation: There is a risk of sampling bias and misinterpretation in data collection and analysis if researchers lack cultural or contextual understanding.

Benefits of quantitative research

Objectivity: A key benefit of quantitative research approach, this objectivity reduces researcher bias and subjectivity, enhancing the reliability and validity of findings.
Generalizability: For quantitative research, the sample size must be large and representative enough to allow for generalization to broader populations.
Statistical analysis: Quantitative research enables rigorous statistical analysis (increasing power of the analysis), aiding hypothesis testing and finding patterns or relationship among variables.
Efficiency: Quantitative data collection and analysis is usually more efficient compared to the qualitative methods, especially when dealing with large datasets.
Clarity and Precision: The findings are usually clear and precise, making it easier to present them as graphs, tables, and figures to convey them to a larger audience.

Limitations of quantitative research

Lacks depth and details: Due to its objective nature, quantitative research might lack the depth and richness of qualitative approaches, potentially overlooking important contextual factors or nuances.
Limited exploration: By not considering the subjective experiences of participants in depth , there’s a limited chance to study complex phenomenon in detail.
Potential oversimplification: Quantitative research may oversimplify complex phenomena by boiling them down to numbers, which might ignore key nuances.
Inflexibility: Quantitative research deals with predecided varibales and measures , which limits the ability of researchers to explore unexpected findings or adjust the research design as new findings become available .
Ethical consideration: Quantitative research may raise ethical concerns especially regarding privacy, informed consent, and the potential for harm, when dealing with sensitive topics or vulnerable populations.

Frequently asked questions

What is the difference between qualitative and quantitative research?

Quantitative methods use numerical data and statistical analysis for objective measurement and hypothesis testing, emphasizing generalizability. Qualitative methods gather non-numerical data to explore subjective experiences and contexts, providing rich, nuanced insights.

What are the types of qualitative research?

Qualitative research methods include interviews, observations, focus groups, and case studies. They provide rich insights into participants’ perspectives and behaviors within their contexts, enabling exploration of complex phenomena.

What are the types of quantitative research?

Quantitative research methods include surveys, experiments, observations, correlational studies, and longitudinal research. They gather numerical data for statistical analysis, aiming for objectivity and generalizability.

Can you give me examples for qualitative and quantitative research?

Qualitative Research Example:

Research Question: What are the experiences of parents with autistic children in accessing support services?

Method: Conducting in-depth interviews with parents to explore their perspectives, challenges, and needs.

Quantitative Research Example:

Research Question: What is the correlation between sleep duration and academic performance in college students?

Method: Distributing surveys to a large sample of college students to collect data on their sleep habits and academic performance, then analyzing the data statistically to determine any correlations.

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