This fact sheet is designed to be a practical step-by-step guide for Extension professionals to help them navigate the process of statistical analysis for any type of data that is derived from any type of survey. The paper will cover some theoretical foundations, while mostly focusing on practical application of the right steps to conduct an analysis. The goal is to empower you to move from raw data to meaningful insights that can inform your programming, demonstrate your impact, and strengthen your accountability to stakeholders. As Majumdar et al. (2020) suggest, a practical evaluation tool and framework is essential for Extension educators to “determine program success and show public value” (Majumdar et al., 2020). This road map will walk you through a systematic process, from preparing your data to interpreting and presenting your results. Each step includes practical tips, checklists and references to the underlying statistical principles. By following this road map, you can ensure that your data analysis is not only statistically sound, but also a powerful tool for telling the story of your program’s success.

The Critical Role of Statistical Literacy in Extension Program Evaluation

In the field of Extension, professionals are constantly engaged in a cycle of program development, implementation and evaluation. The data collected through these efforts are the lifeblood of evidence-based practice, providing the necessary insights to assess program effectiveness, demonstrate impact to stakeholders, and make informed decisions about resource allocation. However, the value of this data is entirely dependent on the appropriateness of the statistical methods used to analyze it. The selection of an incorrect statistical test can lead to a cascade of negative consequences, including invalid conclusions, misallocation of resources, and a loss of credibility with funders and the community. As Taylor (2008) notes, statistical analysis of the results yields valuable information that can be used to improve programs and to demonstrate their impact to stakeholders (Taylor, 2008).

This fact sheet serves as a practical guide for Extension professionals to navigate the often-complex landscape of statistical test selection. It provides a comprehensive overview of data types, a decision-making framework for choosing the right statistical test, and best practices for visualizing data to communicate program impact effectively. By strengthening statistical literacy, Extension professionals can ensure their evaluation efforts are not only rigorous and defensible, but also a powerful tool for driving positive changes in the communities they serve.

For all the steps, including:

1. Preparing your data for analysis
2. Choosing the Right Statistical Test
3. Understanding Your Data and The Four Levels of Measurement
4. The Importance of Normality Testing
5. Other Scenarios for Statistical Analysis in Extension
6. Visualizing Your Data: Telling a Compelling Story

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