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

The t-Test of Differences Between Means:
Paired Sample t-Test for Participant Pre- and Posttests

Step 1: State Null hypothesis

Sometimes it is easier to show that something is false than to show that something is true. Ask a criminal defense lawyer. In statistics, you are always going to have a null hypothesis and a research hypothesis. The null hypothesis is the hypothesis we are going to try to disprove. The research hypothesis states the opposite of what the null hypothesis claims. This is what the researcher hopes to find.

Our null hypothesis (represented as H₀) reads:

H₀ =

The mean score for inhalant use for participants at posttest is not different from the mean score for inhalant use for participants at pretest.

Other ways to state this hypothesis:

H₀ =

The mean difference between the two groups is zero ("null").
H₀ = There is no difference between the means of the two tests. The symbolic representation is H₀ = µ1 - µ2 = 0.

The research hypothesis (represented as H₁) reads:

H₁ = The mean score of inhalant use for participants at posttest is different from the mean score of inhalant use for participants at pretest.

Other ways to state this hypothesis:

H₁ = The mean difference between the two tests is not zero.
H₁ = There is a difference between the means of the two tests. The symbolic representation is H₁ = µ1 - µ2 not equal to 0.