CONTENTS

Table of Contents
Introduction

1. Descriptive Statistics in Evaluation
2. Subgroup Analysis
3. Variable - Are They Related?
4. Correlation
5. The t-Test of Difference Between Means

Supplements
Resources
Glossary

Wading Through the Data Swamp:
Program Evaluation 201

Module Content Objectives Background Comparing Means Attrition Versus Loss to Followup New Information: Change Scores and Participation How To Construct Scatter Plots How To Interpret Scatter Plots Linear Relationship Strength of the Relationship: Pearson's Correlation Coefficient What Do All the Numbers and Plots Mean? Adding Points to a Scatter Plot Lessons Learned: What Jack Should Have Asked His Evaluator What Did Jack Learn About His Program From These Analyses? How Can Jack Use This Statistical Information to Improve His Program? How Can Jack Use This Statistical Information To Better Promote His Program? Module 4 Quiz

Background

The Cool After School Program met over a 9-month period. Different activities were planned for each session, such as sports, guest speakers, and discussions on different substance abuse issues. Participants were required to sign in at the beginning and at the end of each session so that Jack could keep track of the amount of time each participant spent involved in the various activities.

In Modules 1 and 2, we discussed how to calculate means and learned about what means can tell us about our data. In this module, we will be comparing the means for participants' alcohol use at pre- and posttest.

In Module 3, the chi-square statistic showed that there was a relationship between participating in the Cool After School Program and alcohol use at posttest. Now we will try to quantify the strength of this relationship and answer the question, "Is there a correlation between participating in Jack's program and achieving better outcomes?"