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

How To Interpret Scatter Plots

So if I connect the dots, will it look like a map of Italy? No, but it will tell you some things about your program.

This scatter plot may be a little different from other plots you may have seen. We have both negative and positive values on the y-axis (change in alcohol use), because change scores can be either negative or positive. (Remember that negative change in alcohol use is what we would like to see here.)

From the scatter plot, we can see that most of the kids have not attended more than six sessions. Their codes for number of sessions are mostly 1's and 2's. In fact, only two kids attended nearly all the sessions (code 5).

It looks like the data points follow a downward slope. As you read about the different types of relationships, you will learn what this pattern tells us.

Negative Relationship

If the pattern of scores is moving down and to the right, we say there is a negative relationship. This means that as one variable increases, the other decreases. In Jack's case there is a negative relationship between amount of services received and alcohol use. As number of sessions increases, alcohol use decreases. This pattern is IDEAL in Jack's case.

Positive Relationship

If the pattern of scores is moving up and to the right, we say there is a positive relationship. This means that as one variable increases, the other increases. In Jack's case, it would mean that as the number of sessions increases, participants' alcohol use increases.

Also, a positive relationship exists if we find that as the number of sessions decreases, participants' alcohol use decreases. This is a pattern Jack does not want to see.

No Relationship

If the dots representing the scores of change in alcohol use are scattered all over the place or look like a round cloud, then we say that no relationship exists between the two variables. The correlation value of zero indicates that the two variables are not related. This is another pattern that Jack does not want to see.

Summary of Scatter Plot Possibilities

Type of Relationship	Change in Alcohol Use	Change in Services Received
Negative
Negative
Positive
Positive
No relationship	Can't discern a pattern	Can't discern a pattern