What is the difference between qualitative and quantitative data?

The distinction between qualitative and quantitative data is foundational in research methodologies. Qualitative data is inherently descriptive, focusing on characteristics, themes, or subjective observations that provide insights into concepts or experiences. This type of data often comes from interviews, open-ended survey responses, or observations, and it aims to capture the richness and complexity of human experience.

In contrast, quantitative data is numerical in nature and can be measured and analyzed statistically. It encompasses data obtained from experiments, surveys with predetermined response options, or any sources that produce measurable outcomes, such as sales figures or test scores. This type of data is often used to test hypotheses or analyze trends through statistical procedures, which provide more generalized results applicable to populations.

The other options present misconceptions or inaccuracies regarding the nature of qualitative and quantitative data. While qualitative data can certainly give rich insights, it is not universally "more accurate" than quantitative data, as accuracy can depend on the research context and question. Also, the idea that qualitative data involves statistical analysis while quantitative does not is misleading; quantitative data is primarily designed for statistical analysis. Lastly, qualitative data can be gathered through various means beyond controlled experiments, which are typically associated with quantitative approaches. Thus, the correct answer highlights the key differentiation based on the descriptive versus numerical