Distinguish between qualitative and quantitative data and give seminar-appropriate examples for each.

• A. Qualitative data are non-numeric (interviews, themes).
• B. Qualitative uses numbers; quantitative uses words.
• C. Qualitative is more accurate.
• D. Quantitative cannot measure frequency.

Answer: (A)

Distinguishing qualitative and quantitative data comes down to how information is represented: in words or in numbers. Qualitative data are non-numeric and capture qualities, meanings, and patterns described by people, often gathered through interviews, open-ended responses, or detailed observations. In seminar work, you’d analyze qualitative data by coding responses to identify themes or narrative insights, such as how participants describe their experiences or the nuances you see in a classroom interaction.

Quantitative data, on the other hand, are numeric and enable counting, measuring, and statistical comparison. Seminar examples include closed-ended survey responses with numeric scales, experimental measurements, or frequency counts of occurrences, which you can summarize with statistics like averages or percentages.

The statement that qualitative data are non-numeric (for example, interviews and themes) best captures this distinction because it directly contrasts words with numbers. The idea that qualitative uses numbers is inaccurate, and claiming qualitative is inherently more accurate shifts the focus away from data form. Also, saying quantitative cannot measure frequency is false, since frequency is a basic quantitative measure.