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

To the Reader:

My name is Dr. Ernestine Val (my friends call me "E"). I am your host and will guide us through each of these exercises.

We will use the case study approach to work through a HYPOTHETICAL dataset from a HYPOTHETICAL substance abuse prevention program. (While the data are made up, the instruments and analyses are quite real.) By the time we're through, you should have enough information to avoid the problems Jack faced.

The following course is not designed to make you an evaluator. Instead, the goal is to increase your understanding of key concepts and potential pitfalls in evaluation research, so that you can ask the right questions of the right people at the right time and not end up like poor Jack.

What we hope you gain from this Web-based experience is the deserved self-confidence to be an active partner in your program's evaluation. And remember, any evaluator worth his/her fee will gladly work with you to help you understand the finer points of their proposals. There are no stupid questions. Remember, like Jack, you will be paying for the evaluator's service.

Had Jack followed the simple guidance offered in this course, he would have read it critically and not taken the results at face value. He might have asked clarifying questions that may have sent the evaluator back to the computer to undertake some additional analyses.

In Evaluation 101 and 102, we covered the various types of evaluation, data collection methods, and reasons for conducting an evaluation.

Now, at the intermediate level, we will work through a sample substance abuse prevention program evaluation. To the extent possible, we have tried to create a real world evaluation. (We really try to put the "U" in evalUation.)