Data Analysis and Interpretation
The purpose of the data analysis and interpretation phase is to transform the data you have collected during the implementation phase into credible evidence about how your program was developed and its effectiveness in achieving the program objectives.
Analysis can help answer some key questions:
- Has the program made a difference or led to change?
- How big is this change in knowledge, attitudes, beliefs, or behavior?
- Why has the program succeeded or not succeeded in changing knowledge, attitudes, beliefs, or behavior?
This process usually includes the following steps:
- Organizing the data for analysis;
- Describing the data;
- Interpreting the data.
One of the most important issues in interpreting your research findings is understanding how the outcomes relate to the specific activities of the program. This involves making the distinction between association and causation, and the role that can be played by confounding factors in obscuring the evidence. The Data Interpretation note in the Resources Sidebar includes more information on these important issues.
Collaborating with researchers or statisticians experienced in qualitative and quantitative social sciences research is an excellent idea if your team does not have expertise in data analysis. This collaboration would serve the dual purpose of having an independent third party responsible for the analysis and interpretation of results and ensuring that the analysis portion of your program is carried out with the same level of effort and expertise that you have dedicated to all of the other stages of your program.
Criteria for Organizing and Analyzing Data
Short- and Long-Term Outcomes