Qualitative data describes qualities in words, while quantitative data is measured in numbers.
Qualitative data
Describes qualities, characteristics or opinions, in words, images or observations. It answers “why” and “how”. Examples: interview responses, color, taste.
Quantitative data
Numbers that can be measured and counted. It answers “how many” or “how much”. Examples: height, age, test scores.
Methods
- Qualitative: interviews, focus groups, observation.
- Quantitative: surveys with numeric scales, experiments, measurements.
Analysis
Qualitative: coding themes. Quantitative: statistics.
Strengths
Qualitative gives depth. Quantitative gives breadth and precision.
Mixed methods
Many studies use both.
Example
“The service was friendly” (qualitative) vs. “4.5 out of 5” (quantitative).
Qualitative examples
Interview transcripts, open ended survey answers, photographs, field notes and observations. A researcher may ask, “How do patients experience the waiting room?”
Quantitative examples
Test scores, income, temperatures, counts, survey ratings on a scale of 1 to 5 and sales figures. A researcher may ask, “How many patients wait longer than 30 minutes?”
Analysis methods
- Qualitative: thematic analysis, content analysis, grounded theory and coding.
- Quantitative: statistics such as means, correlations, regressions and hypothesis tests.
Sampling
Qualitative studies often use small purposive samples of 10 to 30 people, selected for depth. Quantitative studies need large random samples, chosen to represent a population and allow generalization.
Strengths
- Qualitative: rich context, new ideas and understanding of motives.
- Quantitative: precise numbers, comparisons and testing of hypotheses.
Limits
- Qualitative: less generalizable, and more subject to researcher bias.
- Quantitative: may miss the “why” and depends on the questions asked.
Mixed methods
Many studies combine both, for example surveying 1,000 customers and then interviewing 20 to explain unexpected results.
Data reliability
Quantitative research reports reliability and validity, while qualitative research aims for credibility through member checking and triangulation.
Methods and examples
Qualitative research collects non numerical data such as words, images and observations, using interviews, focus groups, open ended survey questions and field notes. It aims to understand meaning, experience and context, and it is analyzed through coding and themes. Quantitative research collects numerical data that can be counted or measured, such as test scores, ages, incomes or survey ratings on a 1 to 5 scale, and uses statistics to test hypotheses and estimate relationships. Sampling in quantitative studies often relies on probability samples so results can be generalized, while qualitative studies often use smaller purposive samples of 10 to 30 participants chosen for depth.
Strengths, limits and mixed methods
Quantitative methods are strong for comparing groups and measuring size of effects, but they can miss the reasons behind the numbers. Qualitative methods give rich detail, but results are harder to generalize and can be influenced by researcher interpretation. Researchers often use mixed methods, such as a survey followed by interviews to explain unexpected findings. Reliability and validity are used to judge quantitative measures, while credibility, transferability and confirmability are terms used to judge qualitative work. A good research question decides the method: “How many?” suggests quantitative, and “How and why?” suggests qualitative.
Based on data from the Purdue Online Writing Lab and university research methods guides
