Types of Data

Types of Data

There are many ways to collect data to answer your evaluation questions. The data collection technique you select may produce numerical information such as quantitative data, may be more illustrative, such as qualitative data, or might include a combination of the two, such as mixed methods data. Determining what type of data you will need to answer your evaluation questions is an important step in figuring out the technique you will use. In the table below are some quick facts and examples of different types of data you can collect. 



              Quick Facts


Quantitative Data

  • Requires use of statistical analysis
  • Variables can be identified and relationships measured
  • Counted or expressed numerically
  • Often perceived as a more objective method of data analysis
  • Typically collected with surveys or questionnaires
  • Often represented visually using graphs or charts
   An evaluator may wish to measure the knowledge of social skills amongst program participants. He/she may administer surveys to participants to test their knowledge of these social skills.

Qualitative Data

  • Examines non-numerical data for patterns and meanings
  • Often described as being more “rich” than quantitative data
  • Is gathered and analyzed by an individual, it can be more subjective
  • Can be collected through methods such as observation techniques, focus groups, interviews, and case studies

   Evaluators may wish to look at the level of engagement of afterschool staff in program trainings. He/she might conduct interviews of these staff members to capture the level of engagement that each staff member feels they have during the trainings.

Mixed Methods Data

  • May increase the validity of your evaluation
  • May explain unexpected results obtained using only one approach (quantitative or qualitative)
  • Help you capture both process and outcome results
  • May strengthen your analysis
   You may administer a survey to participants which solicits answers that are eligible for statistical analysis as well as conduct a focus group with a sampling of participants to capture any nuances the survey may have missed.



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