How do qualitative data differ from quantitative data?

Qualitative data is primarily descriptive and conceptual, focusing on the qualities or characteristics of a subject rather than on numerical measurement. This type of data often involves insights, opinions, themes, and other non-numeric attributes, making it rich in detail and context. For example, qualitative data might describe user experiences, perceptions, or motivations, providing depth to the understanding of a phenomenon.

In contrast to qualitative data, quantitative data emphasizes numerical values that can be measured precisely, allowing for statistical analysis and more straightforward comparisons. The distinction lies in the essence of what each data type seeks to represent; qualitative data aims to capture subjective experiences and features, whereas quantitative data is about objective measurements and counts.

Recognizing that qualitative data is not necessarily larger in volume reflects a core misunderstanding, as the volume of qualitative data can vary widely based on the research method and purpose. Moreover, while qualitative insights can sometimes be quantified for analysis, doing so compromises the richness and depth of the original qualitative data. Thus, option B accurately defines the nature of qualitative data as descriptive and conceptual, highlighting its focus on qualities rather than quantities.