1 / 16

Independent t-Test

Independent t-Test. CJ 526 Statistical Analysis in Criminal Justice. When to Use an Independent t-Test. Two samples Interval or ratio level dependent variable Either Experimental and control group comparison Or Comparing two separate independent groups (no overlap).

kirby
Télécharger la présentation

Independent t-Test

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

  2. When to Use an Independent t-Test • Two samples • Interval or ratio level dependent variable Either Experimental and control group comparison Or Comparing two separate independent groups (no overlap)

  3. Characteristics of an Independent t-Test • Sample means are hypothesized to be the same. Either • Treatment has no effect, comparing an experimental that received treatment and a control group that did not receive treatment • Or, two independent groups are the same with respect to a DV

  4. Example of an Independent t-Test • A psychologist wants to determine whether diversity training has an effect on the number of complaints filed against employees. He/she randomly assigns 20 employees to a training group, and 20 employees to a control group.

  5. Example of an Independent t-Test -- continued • Number of Groups: 2 • Nature of Groups: independent • Independent Variable: training • Dependent variable: number of complaints

  6. Example of an Independent t-Test -- continued • Dependent Variable and its Level of Measurement: complaints--interval • Target Population: employees • Appropriate Inferential Statistical Technique: t-test • One or two-tailed? Probably one tail

  7. Example of an Independent t-Test -- continued 9. Null Hypothesis: • Mean of exp group – mean of control group = 0 10. Alternative Hypothesis: Mean of experimental group minus mean of control group does not equal 0 11. Decision Rule: • If the p-value of the obtained test statistic is less than .05, reject the null hypothesis

  8. Example of an Independent t-Test -- continued 12. Obtained Test Statistic: t 13. Decision: accept or reject null hypothesis Null hypothesis—training did not affect complaints, comparing experimental and control groups Alternative, one tail—training reduced complaints as compared to a control group without training See p. 725

  9. Results Section • The results of the Independent t-Test using diversity training as the independent variable and number of complaints filed against employees were statistically significant, t (18) = 2.35, p < .05. • D.f. degrees of freedom = n(group 1)+n(group 2) - 2

  10. Discussion Section • It appears that employees undergoing diversity training have fewer complaints filed against them. • Or, if the null hypothesis was retained, the conclusion would be that diversity training did not affect the number of complaints filed

  11. SPSS Independent-Samples t-Test Procedure • Analyze, Compare Means, Independent-Samples t-Test • Move DV over to Test Variables • Move IV over to Grouping Variable • Enter numerical values of the IV under Define Groups

  12. SPSS Independent-Samples t-Test Sample Printout T-Test

  13. SPSS Independent-Samples t-Test Printout • Group Statistics • DV • Levels of IV • N: Sample size • Mean • Standard Deviation • Standard Error of the Mean

  14. SPSS Independent-Samples t-Test Printout -- continued • Levene’s Test for Equality of Variances • Test for homogeneity of variance assumption • t-Test for Equality of Means • If Levene test is not significant • Equal variances assumed • If Levene test is significant • Equal variances not assumed

  15. SPSS Independent-Samples t-Test Printout -- continued • t-Test for Equality of Means • t: obtained test statistic • df: degrees of freedom • Sig: p-value • Divide by 2 to get one-tailed p-value • Mean Difference • Difference between the two sample means

  16. SPSS Independent-Samples t-Test Printout -- continued • Standard Error of the Difference • 95% Confidence Interval of the Difference • Lower • Upper

More Related