In community needs assessments, data can be qualitative, quantitative, or both. Which statement is true about data types?

In community needs assessments, data can be qualitative, quantitative, or both. Which statement is true about data types?

• A. Qualitative data only
• B. Both qualitative and quantitative data
• C. Quantitative data only
• D. Neither qualitative nor quantitative data

Answer: (B)

Data in community needs assessments can be qualitative, quantitative, or both. Qualitative data captures people’s experiences, beliefs, and the context behind needs through interviews, focus groups, and open-ended survey responses. Quantitative data provides measurable information—counts, percentages, and scale ratings—from structured surveys, census data, and program records. Using both types gives a fuller view: numbers show how widespread an issue is, while narratives explain why it exists and what factors contribute. This combination also supports triangulation, strengthening conclusions and guiding more effective interventions. So, the true statement is that data types can be both qualitative and quantitative. Limiting to only one type would miss either depth or breadth, while excluding both would ignore established methods for understanding communities.

Data in community needs assessments can be qualitative, quantitative, or both. Qualitative data captures people’s experiences, beliefs, and the context behind needs through interviews, focus groups, and open-ended survey responses. Quantitative data provides measurable information—counts, percentages, and scale ratings—from structured surveys, census data, and program records. Using both types gives a fuller view: numbers show how widespread an issue is, while narratives explain why it exists and what factors contribute. This combination also supports triangulation, strengthening conclusions and guiding more effective interventions. So, the true statement is that data types can be both qualitative and quantitative. Limiting to only one type would miss either depth or breadth, while excluding both would ignore established methods for understanding communities.