Quantitative and Qualitative Data
Quantitative data is described in numbers and shows how often something occurs or to what degree a phenomenon exists. Quantitative data:
- Answers, “How many?” “How often?”
- Measures levels of behavior and trends.
- Is objective, standardized, and easily analyzed.
- Is easily comparable to similar data from other communities and levels.
- Examples: statistics, survey data, records, archival data.
Qualitative data is described in words and explains why people behave or feel the way they do. Qualitative data:
- Answers, “Why?” “Why not?” or “What does it mean?”
- Allows insight into behavior, trends, and perceptions.
- Is subjective and explanatory.
- Helps interpret quantitative data, provides depth of understanding.
- Examples: focus groups, key informant interviews, case studies, story-telling, observation.
Communities may not have quantitative data, particularly for certain at-risk groups (e.g., homeless, LBGT, and some minority groups like tribes); so qualitative data can be very useful in these situations. In fact, many epidemiologists and evaluators recommend collecting both quantitative and qualitative data. This “mixed method” provides a much more in-depth understanding of the population groups or communities being assessed because it allows you to collect the same information across several individuals/groups (or other units of measure). In addition, usually the quantitative data generates responses to questions that are created by the researcher, whereas the qualitative is more open-ended with responses that are generated by the respondents; so combining the two approaches offers a way to understand the quantitative data from the perspective of the respondent.
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