What is the main difference between qualitative and quantitative data in TandE?

The distinction between qualitative and quantitative data is pivotal in Test and Evaluation practices. Qualitative data is characterized as descriptive and subjective; it captures the qualities, attributes, or characteristics of an aspect under review. This type of data often involves opinions, experiences, and observations, providing a richer understanding of a particular phenomenon. It is typically gathered through interviews, open-ended surveys, or focus group discussions, where the insights gained are more about understanding context rather than providing hard numbers.

On the other hand, quantitative data is numerical and objective, allowing for measurement and statistical analysis. This data is usually collected through structured methods like tests, surveys with closed-ended questions, or experiments where the outcomes can be quantified and assessed objectively. Because of this objectivity, quantitative data can often be analyzed using statistical methods to produce meaningful findings that can be generalized across larger populations.

Thus, the correct identification of quantitative data as numerical and objective, and qualitative data as descriptive and subjective, captures the essence of their differences accurately. This understanding is crucial in the realm of Test and Evaluation, as each data type serves different purposes and offers varied insights into the subject matter being tested or evaluated.