Find the Patterns: Facts

Your raw data likely reflects the outputs referenced in your logic model. Analyzing raw data will help you measure and resolve issues related to management, or the way in which your program is run. For example, raw data can show you the number of individuals who registered for the program and the number of individuals who completed the program.

To answer your strategic guiding questions and gain a deeper understanding of your program’s impact, you will need to take your raw data and transform it using a combination of basic arithmetic and descriptive statistics to reveal patterns—both those that you expect to see and those that may be surprising.

A helpful tool in statistical analysis is the “facts-stats-trends” framework:

  • Facts: Counts, or sums, of numbers
  • Stats: Basic descriptive statistics (mean, median, mode, distribution)
  • Trends: Looking at data over time (e.g., percent change, percent difference)
    • Within the same group at different points in time
    • Between groups at the same time or at different points in time

Facts provide a high level summary of your raw data. Results provide “nice to know” information and help you familiarize yourself with your data set.

  • 50 participants
  • $10,000 raised
  • 100 email clicks

You can also express your raw data in ratios (usually a percentage or fraction) to provide more context. This may require some division:

  • 50 participants out of 100 registered = 50% participation rate
  • $10,000 raised compared to $5,000 last year = double the money raised
  • 100 clicks out of 1,000 email recipients = 10% click-through rate

If you previously set goals or benchmarks for the data you collected, compare them to your results:

  • 50 participants, 50% of goal (100 participants)
  • $10,000 dollars raised, 100% of goal ($10,000)
  • 100 email clicks, 25% of goal (400 clicks)