Which statement correctly differentiates secondary analysis in research?

• A. Secondary analysis reuses existing data to draw new conclusions.
• B. Primary data are original data collected by researchers; secondary analysis reuses existing data to draw new conclusions.
• C. Primary data are always numerical; secondary analysis is always qualitative.
• D. Secondary analysis requires no data and is purely theoretical.

Answer: (B)

The main idea here is to understand what counts as primary data versus secondary analysis. Primary data are original data collected by researchers specifically for the study at hand, with new observations or measurements made to answer a particular question. Secondary analysis involves reusing data that were collected for a different purpose to address a new question or test a different hypothesis, without collecting new observations.

The statement that primary data are original data collected by researchers and secondary analysis reuses existing data to draw new conclusions captures this distinction precisely. It makes clear what is produced and how it’s used in each case, which is the core difference researchers consider when planning studies or reanalyzing data.

Other descriptions drift from this distinction in important ways. For example, claiming primary data are always numerical ignores qualitative data collected directly by researchers, or suggesting secondary analysis is purely theoretical ignores the actual data that are reexamined.