Qualitative vs Quantitative Research | Methods & Differences
Qualitative and quantitative research use different methods to explore research questions. Qualitative research involves non-numerical data, such as interviews or participant observation. Quantitative research relies on numerical data gathered through surveys or experiments.
| Property | Qualitative Research | Quantitative Research |
|---|---|---|
| Focus | Gaining deep insight into a new or nuanced topic | Testing hypotheses, exploring cause-and-effect relationships, exploring patterns |
| Type of data | Narrative (e.g., text, pictures, audio and video recordings) | Numerical |
| Data collection methods | Interviews, participant observation, focus groups, collection of documents | Questionnaires, surveys, experiments |
| Study location | Can take place in naturalistic settings | Generally takes place in controlled settings |
| Sample size | Small, targeted sample | Large, random sample |
| Data analysis | Thematic analysis, coding | Statistical analysis |
| Strengths | High validity | High reliability and generalizability |
| Weaknesses | Time-consuming, lacks generalizability, subjective | Cannot study phenomena that cannot be expressed numerically, lacks validity |
Differences between qualitative and quantitative research
Qualitative and quantitative research use distinct methods to collect and analyze data. Quantitative research concerns numerical data, whereas qualitative research involves non-numerical data (e.g., text, pictures, audio and video recordings).
Quantitative research is objective—scientists using quantitative methods do their best to avoid bias and assume that there is a ground truth that can be uncovered through careful data collection and experimentation. This mindset is referred to as positivism.
On the other hand, qualitative research explores questions related to the subjective experiences of individuals—why people feel and behave in certain ways. Qualitative methods allow for differences in individual opinion, which is called interpretivism.
When to use quantitative vs qualitative research methods
The research methods you use for your study will depend on your research questions and what kind of insight you hope to gain. If you’re hoping to test a theory or hypothesis or capture numerical trends, quantitative research methods may be more appropriate. If instead you’d like to gain a deeper understanding about a new or nuanced topic, you may choose to use qualitative methods.
Consider the following examples of how different research questions can be addressed with quantitative and qualitative methods:
| Research question | Quantitative approach | Qualitative approach |
|---|---|---|
| How does class size impact academic performance in high school students? | Assess correlations between class size and standardized test scores across different schools | Run focus groups and ask students about how they feel class size impacts their learning experience |
| How do nature programs impact anxiety symptoms in young children? | Separate children into a study group and a control group and compare changes in pre- and post-intervention scores on a child anxiety scale | Observe children’s behavior and interactions throughout a six-week program and note emerging themes and patterns |
| How does remote work impact employee productivity? | Analyze productivity metrics before and after a workplace switches to a remote work structure | Conduct virtual interviews with employees to understand their attitudes toward remote work and how it helps or hinders their ability to do their job |
Mixed methods research
Some questions cannot be answered by qualitative or quantitative methods alone. Researchers will sometimes use a mixed methods approach that combines both quantitative and qualitative techniques.
When adopting a mixed methods approach, it’s important to consider how and when qualitative and quantitative findings will be combined and interpreted.
Qualitative vs quantitative data
A key difference between qualitative and quantitative methods is the type of data they use.
Qualitative data collection methods
Qualitative methods use non-numerical data. Some common examples of qualitative data are outlined in the table below.
| Type of data | Description |
|---|---|
| Observations | Observational data are collected by watching a group or individual and recording what is seen or heard |
| Interviews | Interviews involve asking a person a series of questions and recording their responses |
| Focus groups | Focus groups are similar to interviews, but the researcher speaks to two or more people at once |
| Written documents | Written documents include many forms of text, including books, historical records, diaries, and letters |
| Photos, audio recordings, and videos | These non-textual data are often rich in context and can be collected by a researcher or may already exist |
Quantitative data collection methods
Quantitative data are operationalized or measured using numbers.
| Type of data | Description |
|---|---|
| Observations | Observational data in quantitative research are obtained by observing a phenomenon and recording it quantitatively (e.g., count) |
| Surveys | Surveys may contain multiple choice questions, rating scales, Likert scales, and demographic questions |
| Measurement instruments | Measurement instruments or devices can be used to numerically capture a phenomenon; they can range from a scale used to record weight to an MRI machine used to record brain activity |
Qualitative vs quantitative data analysis
Because qualitative and quantitative methods involve different types of data and answer different types of questions, the analysis techniques used for each also differ.
Qualitative data analysis
Qualitative data are non-numeric and generally expressed in words (though they also may include pictures, audio, or videos). Analyzing qualitative data generally involves organizing and summarizing data to extract patterns and themes.
Some common techniques to analyze qualitative data are as follows:
- Content analysis: involves describing how frequently certain words or ideas occur in a qualitative dataset
- Thematic analysis: used to identify high-level themes or recurring patterns in qualitative data
- Discourse analysis: analyzing written or verbal communication to explore how ideas are communicated in different settings
Quantitative data analysis
Quantitative data are analyzed using statistical methods. After preparing data for analysis (which may involve cleaning and transforming different variables), researchers use a combination of descriptive and inferential statistics to answer their research questions.
Descriptive statistics describe the data. Descriptive statistics include proportions, central tendency (e.g., mean, median, and mode), and range (e.g., standard deviation).
Inferential statistics are instead used to make predictions about a population or test hypotheses. They generally involve identifying patterns in your sample data and determining how likely it is that these patterns reflect true properties of the general population.
Frequently asked questions about qualitative vs quantitative research
- How do I decide between qualitative and quantitative research?
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Qualitative and quantitative research methods are used to investigate different types of research questions.
Quantitative methods are best if:
- The topic you’re studying can easily be expressed using numbers
- You want to use statistics to test a hypothesis
Qualitative methods are best if:
- The topic you’re studying cannot be expressed numerically
- You’re studying a new research area with limited existing theories
- You want to gain deep insight into a nuanced issue
- How do I analyze qualitative data?
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Qualitative data are generally narrative in nature. They may include interview transcripts or experimenter observations. Different approaches exist to analyze qualitative data, but common steps are as follows:
- Organize the data
- Code the data, sorting it into relevant categories
- Extract and interpret key ideas
Common qualitative data analysis techniques include content analysis, thematic analysis, and discourse analysis.
- What is a research design?
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The research design is the backbone of your research project. It includes research objectives, the types of sources you will consult (i.e., primary vs secondary), data collection methods, and data analysis techniques.
A thorough and well-executed research design can facilitate your research and act as a guide throughout both the research process and the thesis or dissertation writing process.
- What is operationalization?
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Operationalization is when you define how a variable will be measured. Operationalization is especially important in fields like psychology that involve the study of more abstract ideas (e.g., “fear”).
Because fear is a construct that cannot be directly measured, a researcher must define how they will represent it. For example, in studies involving mice, fear is often operationalized as “”how often a mouse freezes (i.e., stops moving) during an experiment.”
Operationalization can be used to turn an abstract concept into a numerical form for use in quantitative research.
Some operationalizations are better than others. It is important to consider both reliability and validity (how consistent and accurate a measurement is, respectively) when operationalizing a construct.
