1. CJ 526 Statistical Analysis in Criminal Justice
Dependent t-Test
CJ 526 Statistical Analysis in Criminal Justice

2. When to Use a Dependent t-Test
Two Dependent (related) Samples
Repeated-Measures Design (before-after)
Matched-Subjects Design

3. Example of a Dependent t-Test
A forensic psychologist wants to determine whether physical exercise in a boot camp program has an effect on muscular strength. He/she measures the number of pull-ups 25 program participants complete at the beginning of the program (M = 3.28, SD = 1.88) and at the end of the program (M = 3.6, SD = 1.73).

4. Example of a Dependent t-Test -- continued
Number of Samples: 2 (before & after)
Nature of Samples: dependent (same subjects at two different points in time)

5. Example of a Dependent t-Test -- continued
3. Independent Variable: participation in boot camp--exercise
4. Dependent Variable and its Level of Measurement: number of pull-ups (ratio)
5. Target Population: boot camp participants

6. Example of a Dependent t-Test -- continued
6. Appropriate Inferential Statistical Technique: t test, related samples
Null Hypothesis: no difference between the groups before and after boot camp exercise
Alternative Hypothesis: there will be a difference, boot camp participants will be able to do more pull ups after training
Decision Rule:
If the p-value of the obtained test statistic is less than .05, reject the null hypothesis, one-tail test

7. Example of a Dependent t-Test -- continued
10. Obtained Test Statistic: t
Decision: accept or reject null hypothesis
D.f. = n-1
(in this case n – 1 = 25 – 1 = 24

8. Results Section
The results of the Dependent t-Test involving participating in a physical exercise program as the independent variable and number of pull-ups as the dependent variable were not statistically significant.

9. Discussion Section
It appears that participating in a physical exercise program did not have an effect on developing muscular strength among participants in a boot camp program.

10. SPSS Paired-Samples t-Test Procedure
Analyze, Compare Means, Paired-Samples t-Test
Move pair of variables over to Paired Variables

11. SPSS Paired-Samples t-Test Sample Printout

12. SPSS Paired-Samples t-Test Printout
Paired Sample Statistics
Paired variables
Mean N
Standard Deviation
Standard Error of the Mean

13. SPSS Paired-Samples t-Test Printout -- continued
Paired Samples Correlations
Paired variables N
Correlation
Sig
p-value of correlation coefficient

14. SPSS Paired-Samples t-Test Printout -- continued
Paired Samples Test
Paired variables
Paired Differences
Mean of the Difference
Standard Deviation of the Difference
Standard Error of the Mean of the Difference
95% Confidence Interval of the Difference
Lower
Upper

15. SPSS Paired-Samples t-Test Printout -- continued
t: obtained test statistic
df: degrees of freedom
Sig: p-value
Divide by 2 to get one-tailed p-value