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 Introduction Reported Use of Marijuana Missing Data Analysis of Marijuana Use Subgroup Analysis Standard Deviation What Did Jack Learn From This Analysis? Lessons Learned: What Jack Should Have Asked His Evaluator How Can Jack Use This Statistical Information To Improve His Program? How Can Jack Use This Statistical Information To Promote the Results of His Program? Module 2 Quiz

Analysis of Marijuana Use

Okay, so Jack is looking at 48 kids instead of 50. Let's plot the pre- and posttests for the participants.

The mean for the pretest was 1.77 times per week and the mean for the posttest was 2.71 times per week. (Remember that the mean is the total days of marijuana use divided by number of responses.)

Based on these data, it would look as though Jack's program was not effective at all. The posttest mean is actually higher than the pretest mean. In other words, the kids were smoking marijuana more often after being in his program.

Jack was mortified. But when he consulted me, I told him to cheer up. It might not be that bad.

He needs to look at other statistical information in addition to the overall means. The first thing is to break data down into subgroups, which is called subgroup analysis. This way we can see whether the group scores are concealing differences in the outcomes among different groups. Jack should then take a look at the standard deviations.