Which statement best differentiates qualitative data from quantitative data?

• A. Qualitative data are numerical (test scores); quantitative data are descriptive (interviews, open-ended responses).
• B. Qualitative data are descriptive (interviews, open-ended responses); quantitative data are numerical (test scores).
• C. Both data types are numerical but used for different aims.
• D. Quantitative data are numerical, while qualitative data are not useful for analysis.

Answer: (B)

The main idea is that data differ in whether they describe qualities or provide numbers. Qualitative data capture descriptions, meanings, and characteristics from participants—think interviews or open-ended responses where you describe themes or categories. These are analyzed by looking for patterns and how those descriptions relate to concepts, not by arithmetic.

Quantitative data are numerical measurements or counts, such as test scores, reaction times, or survey ratings on a numeric scale. This type of data is suited to statistical analysis, comparisons, and measuring the extent or frequency of something.

So the best statement is that qualitative data are descriptive and collected through methods like interviews or open-ended responses, while quantitative data are numerical, such as test scores. The idea that both are numerical or that qualitative data are not useful for analysis doesn’t fit how these data types are used in research.