Qualitative or Quantitative Data?

The type of data you collect depends on the question you want to answer and your resources. As discussed in Module Four  (click here to review this module) there are two types of data, qualitative and quantitative. Both types of data have strengths and limitations, 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 numerical information and the analysis involves statistical techniques. The type of data you collect guides the analysis process.

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

An example of quantitative data would be if you administered 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 you would use statistical techniques to draw conclusions about participant satisfaction.

Below are two tables detailing the strengths and limitations of both types of data.

Qualitative Data

Strengths

Limitations
  • 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 which can be used to identify patterns of behavior
  • May lend itself to working with smaller populations, which 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/collection

 

Quantitative Data

Strengths

Limitations
  • It is clear and specific
  • If properly analyzed, quantitative data is accurate and reliable
  • Can be easily communicated via charts and graphs
  • 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
  • Requires some expertise with statistical analysis