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

Independent Samples t-Test for Posttest Data

Let's go through the t-test calculations to determine whether there is a statistically significant difference between the two means at posttest. (This is the last one. I promise! The "t" in t-test does not stand for "torture.")

Let's see if the changes we see in the graph below are meaningful.

This compares the participants' mean to the comparison group's mean at posttest. It looks at different groups at the same time.

The only way to find out whether the means from the participant and comparison groups are statistically significant is to calculate an independent t-test for the posttest data. When you are doing statistical analyses for a program, you must have a comparison group. This allows you to ask, "Compared to what?"

For example, the participant group's inhalant use went down, compared to WHAT? Ideally, it would go down, compared to the comparison group's inhalant use.