Credible data is the key to getting your evaluation questions answered.
Data can also be daunting! So get ahead of the game by having a plan for your data collection and analysis.
Credible data analysis always includes a systematic process for the collection, screening, coding, exploration, investigation, and application of statistical or logical tools to interpret the relationship between variables or groups.
Data can include:
- Quantitative Data (data expressed by a number)
- Qualitative Date (data that is not expressed numerically; categorical data)
It is important to know how you plan to analyze your data before you collect it. It will save you both time and headaches. The resources below should help you get started.
Data Analysis Resources
- Analyzing and Interpreting Data (PDF)
University of Wisconsin Extension presentation addressing the key concepts of and steps in the data analysis process.
- Analyzing Quantitative Data (PDF)
University of Wisconsin Extension tip sheet (6 pages) that provides instructions for common mathematical techniques that can make your evaluation data more understandable.
- What is the Difference Between N and n? (PDF)
Penn State Extension tip sheet on how to describe samples.
- Math Helpers (PDF)
An example of how to manually calculate differences for a 5-point Likert-type scale.
- Quantitative Data Analysis: An Introduction (PDF)
Instructional guide produced by the United States General Accounting Office, Program Evaluation and Methodology Division.
- Making Sense of Answers to Open-Ended Questions (PDF)
University of Wisconsin Extension tip sheet with 10 steps to analyze qualitative responses to open-ended questions.
- Percentage Difference Tip Sheet (PDF)
A basic tutorial on the steps for calculating percentage differences.