Describe the difference between qualitative and quantitative data.

Qualitative data encompasses characteristics or attributes that can be observed but not measured numerically. This type of data often includes descriptions, labels, or categories that help identify qualities or properties of a subject, such as color, texture, opinion, or behavior. For example, responses from interviews or open-ended survey questions are typically qualitative, as they convey rich, descriptive information about people's thoughts or experiences.

In contrast, quantitative data is expressed in numerical form and can be measured and analyzed statistically. This type of data is objective and allows for clear comparisons and calculations, such as height, weight, temperature, or test scores. Since it can be quantified, quantitative data supports a wide range of analytical techniques, making it essential for statistical analysis.

This distinction highlights the different purposes and methods used in research: qualitative data seeks to provide insight into complex phenomena and human behavior, while quantitative data seeks to offer a more definitive and measurable view of those phenomena. Understanding this difference is crucial for analyzing data properly and selecting the appropriate research methods and frameworks.