Which statement correctly contrasts qualitative and quantitative data collection?

• A. Qualitative collects rich non-numeric data; quantitative collects numeric data suitable for statistical analysis.
• B. Qualitative uses standardized instruments; quantitative uses unstructured interviews.
• C. Qualitative is always exploratory; quantitative is always confirmatory.
• D. Qualitative data cannot be analyzed statistically.

Answer: (A)

The main idea being tested is how qualitative and quantitative data differ in what is collected and how it’s used. Qualitative data focus on rich, non-numeric information that reveals context, meaning, and participant perspectives—think interview quotes, field notes, or image-based data. Quantitative data yield numeric measurements that are suitable for statistical analysis, such as counts, scales, or measured values. This contrast—that qualitative data are descriptive and interpretive, while quantitative data are numeric and analysable with statistics—is what makes the statement the best description.

Qualitative methods often involve unstructured or semi-structured interactions to explore how people experience a phenomenon in depth, whereas quantitative methods rely on standardized instruments to produce comparable numbers across cases. While the other statements try to describe differences, they oversimplify or misstate common practice: standardized instruments are more typical in quantitative work, and unstructured interviews are common in qualitative work; and both traditions can be exploratory or confirmatory depending on the study design. Moreover, qualitative data can be analyzed in ways that produce statistical insights (through coding and quantification), so claiming they cannot be analyzed statistically isn’t accurate.