1. Significance Testing Difference between two means

2. Review What does significance mean? Why do we use the symbol P<.05 to indicate significance?

3. Defining significance An event is very unlikely to have happened by chance IF the null hypothesis is true.

4. Practice Matching An inferential statistical test used to evaluate the difference between two means Indicates little or no relation between the variables A symmetrical, bell-shaped distribution having half the scores above the mean and half the scores below the mean. A hypothesis that says that all differences between groups are due to chance (i.e., not the operation of the IV) Accepting the experimental hypothesis when the null hypothesis is true 15.1 Normal distribution[hint][hint] 15.2 Zero correlation[hint][hint] 15.3 Null hypothesis[hint][hint] 15.4 t test[hint] [hint][hint] 15.5 Type I error[hint][hint]

5. Objectives What is the logic of the t-test? What is the difference between a one-tailed and a two-tailed test? How do we match our t-test to our experimental design?

6. T-test What is the logic: Compare distance between the means to overall variability in the scores (between- group variability in relation to error variability) Decide on a cut-off (less than 5 chances in 100; less than 1 chance in 100) – significance level or alpha level

7. One-Tailed v two tailed tests The tails of the t-distribution Making predictions: –Pros and cons – Power v Certainty (Type 1 and Type 2 errors)

8. Matching t-test to design Between Groups – Independent samples Matched Groups – Repeated measures Within Groups – Repeated measures

9. Selecting topics for our projects Problems: –Correlation –Disorders, not behaviors –Not really do-able –Not “interesting” from a psychological standpoint Topic not really “psychological” Results already pretty clear