Qualitative or Quantitative Data?

Qualitative or Quantitative Data?

The type of data collected depends on the question to be answered and the available resources. As discussed in Module 4 (click here to review this module), there are two types of data: qualitative and quantitative. Both types of data have strengths and limitations and may be appropriate for different settings, evaluation designs, and evaluation questions.

Qualitative data consist of words and narratives. The analysis of qualitative data can come in many forms including highlighting key words, extracting themes, and elaborating on concepts. Quantitative data are made of numerical information, the analysis of which involves statistical techniques. The type of data collected guides the analysis process.

One example of qualitative data would be a focus group with parents participating in an education program conducted to understand participant perceptions. In this case, the data collected were probably narrative in form, so qualitative techniques would be necessary to analyze the transcripts for content and themes relevant to the program.

An example of quantitative data would be a satisfaction survey asking participants to rate their experience on a scale of 1 to 5. In this case, the data would be numeric in form, and statistical techniques would be necessary to draw conclusions about participant satisfaction.

Qualitative Data

Advantages

Disadvantages

  • Can give a nuanced understanding of the perspectives and needs of program participants
  • Can help support or explain results indicated in quantitative analysis
  • Source of detailed or “rich” information that can be used to identify patterns of behavior
  • May lend itself to working with smaller populations; may not be representative of larger demographics
  • Data analysis can be time consuming
  • Analysis can be subjective; there is potential for evaluator bias in analysis and collection

Quantitative Data

Advantages

Disadvantages

  • Clear and specific
  • Accurate and reliable if properly analyzed
  • Can be easily communicated as graphs and charts
  • Many large datasets already exist that can be analyzed
  • Data collection methods provide respondents with a limited number of response options
  • Can require complex sampling procedures
  • May not accurately describe a complex situation
  • Some expertise with statistical analysis required

The analysis of qualitative data is beyond the scope of this module. For a detailed explanation of one process, see this link.

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