Qualitative vs. Quantitative Research: Differences, Examples, and When to Use Each

Qualitative and quantitative research are the two main approaches to collecting and analyzing data in research. Quantitative research collects numerical data and uses statistics to measure, compare, and test relationships. Qualitative research collects non-numerical data, such as words, observations, and images, to explore meanings, experiences, and reasons. Understanding the difference between qualitative and quantitative research is a foundation of research design, because the approach a study takes shapes its questions, its sample, its data collection, and the way its findings are judged.

This article covers the following:

• What quantitative research and qualitative research are, with examples of each
• The difference between qualitative and quantitative data, including whether a survey is qualitative or quantitative
• A side-by-side comparison of the two approaches
• How mixed methods research combines them
• How to choose between a qualitative or quantitative approach, and common mistakes to avoid

What Is Quantitative Research?

Quantitative research answers questions about how much, how many, how often, and whether a relationship exists. It converts observations into numbers and analyzes them statistically, usually to test a hypothesis. Typical methods include experiments, surveys with closed-ended questions, structured observation, and analysis of existing numerical datasets.

A study that measures how a new exercise program changes the blood pressure of 300 participants, comparing an intervention group with a control group, is quantitative. Its strengths are that results can be generalized to a population when the sample is chosen well, that the methods can be replicated, and that findings can be tested for statistical significance. Its limitations are that numbers can miss context and meaning, and that findings depend heavily on how well the measurement tools capture the concept being studied. How concepts become measurable variables is explained in Operational and Conceptual Definitions in Research, and the roles of the variables in such a study are covered in Independent vs. Dependent Variables.

What Is Qualitative Research?

Qualitative research answers questions about why and how, and about what an experience is like. It explores people’s perspectives, behaviors, and the contexts in which they occur. Common methods include in-depth interviews, focus groups, participant observation, and analysis of documents or recordings. The data are typically analyzed by identifying patterns and themes, using approaches such as thematic analysis or content analysis.

A study that interviews 15 nurses about how they experience night shifts, and identifies the themes in their accounts, is qualitative. Its strengths are depth, attention to context, and the flexibility to follow unexpected findings. Its limitations are that samples are usually small, so findings are not statistically generalizable, and that the analysis involves the researcher’s interpretation, which has to be handled transparently.

Qualitative vs. Quantitative Data

The two approaches are built on two kinds of data. Quantitative data are numerical, such as blood pressure readings, test scores, or the number of hospital visits. Qualitative data are descriptive, such as interview transcripts, open-ended survey responses, field notes, or photographs. Qualitative and quantitative analysis then follow different routes: statistical tests for numerical data, and thematic or content analysis for descriptive data.

Qualitative and quantitative data in research are not always tied to one approach. Qualitative data can be coded and counted, and quantitative studies often include categories as well as measurements. What matters is how the data are collected and what question they are used to answer.

Is a Survey Qualitative or Quantitative?

A survey can be either, depending on its questions. Closed-ended questions, such as rating satisfaction on a five-point scale, produce data that can be counted and analyzed statistically, which makes them quantitative. Open-ended questions, where respondents write their answers in their own words, produce qualitative data. Many surveys combine both.

Qualitative vs. Quantitative Research at a Glance

<table style="width:100%; border-collapse:collapse;">
  <thead>
    <tr>
      <th style="border:1px solid #ddd; padding:10px; text-align:left;">Criteria</th>
      <th style="border:1px solid #ddd; padding:10px; text-align:left;">Quantitative Research</th>
      <th style="border:1px solid #ddd; padding:10px; text-align:left;">Qualitative Research</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Main purpose</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Measure, compare, and test hypotheses</td>
      <td style="border:1px solid #ddd; padding:10px;">Explore meanings, experiences, and reasons</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Typical question</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">How many? How much? Is there a relationship?</td>
      <td style="border:1px solid #ddd; padding:10px;">Why? How? What is it like?</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Data</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Numerical</td>
      <td style="border:1px solid #ddd; padding:10px;">Words, images, observations</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Sample</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Usually larger, often randomly selected</td>
      <td style="border:1px solid #ddd; padding:10px;">Usually smaller, often purposively selected</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Data collection</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Experiments, structured surveys, existing datasets</td>
      <td style="border:1px solid #ddd; padding:10px;">Interviews, focus groups, observation, documents</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Analysis</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Statistical analysis</td>
      <td style="border:1px solid #ddd; padding:10px;">Thematic or content analysis</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Reasoning</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Often tests a theory (deductive)</td>
      <td style="border:1px solid #ddd; padding:10px;">Often builds understanding or theory (inductive)</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Quality criteria</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Reliability and validity</td>
      <td style="border:1px solid #ddd; padding:10px;">Credibility, transferability, dependability, confirmability</td>
    </tr>
    <tr>
      <td style="border:1px solid #ddd; padding:10px;"><strong>Findings</strong></td>
      <td style="border:1px solid #ddd; padding:10px;">Generalizable when the sample is representative</td>
      <td style="border:1px solid #ddd; padding:10px;">Rich and contextual, not statistically generalizable</td>
    </tr>
  </tbody>
</table>

The sampling choices that follow from each approach are discussed in Sampling Methods in Research, and the quality criteria for quantitative work are explained in Reliability vs. Validity in Research. Qualitative studies are commonly judged by whether their findings are credible, transferable to other settings, dependable, and confirmable.

Mixed Methods Research

Mixed methods research combines qualitative and quantitative approaches in a single study, so that each compensates for the other’s limitations. Numbers can show how widespread a pattern is, while interviews can explain why it occurs. The most common designs are:

• Convergent design: both kinds of data are collected at the same time and compared.
• Explanatory sequential design: quantitative data are collected first, and qualitative data are then used to explain the results.
• Exploratory sequential design: qualitative data are collected first to explore a topic, and the findings are then used to build a quantitative study, such as a survey instrument.

Mixed methods research takes more time and requires skills in both approaches, so it is best chosen when the research question genuinely needs both kinds of evidence. How these choices fit into a full study plan is explained in What is Research Design?.

How to Choose a Qualitative or Quantitative Approach

In research design, qualitative, quantitative, and mixed methods approaches are the three main options, and the research question should lead the choice, not the other way around. Whether a project is better suited to quantitative or qualitative research depends on what the question needs to find out.

• Choose quantitative when the question asks about amounts, differences, or relationships, and when a measurable outcome can be defined and tested.
• Choose qualitative when the question asks about experiences, meanings, or processes, or when the topic is new and not yet well understood.
• Choose mixed methods when one approach alone cannot answer the question fully.

Practical factors matter too, including the time available, access to participants, the researcher’s skills, and what the intended journal or audience expects. Whichever approach is chosen, the manuscript should describe it clearly, along with its limitations, which How to Write Limitations of the Study discusses.

Common Mistakes to Avoid

• Choosing the method before defining the research question
• Assuming a survey is quantitative without checking whether its questions are closed or open-ended
• Judging qualitative research by quantitative standards, such as expecting large random samples
• Claiming statistical generalizability from qualitative findings
• Using a quantitative instrument without checking its reliability and validity for the study’s population
• Calling a study mixed methods when the two kinds of data are never actually integrated
• Describing the method too briefly in the manuscript, leaving reviewers unable to judge the findings

Final Thoughts

Qualitative and quantitative research are not rivals. They answer different kinds of questions, and each is rigorous when its methods fit its aims. A clear match between the research question, the approach, and the way the work is reported is what makes a study convincing to reviewers. Researchers preparing a manuscript can also benefit from a language and clarity review so that the design and methods come through precisely, and AJE’s editing services help ensure that a study’s approach and findings are communicated as clearly as they were designed.