1. Chapter 6 Introduction to Hypothesis Testing

2. Hypothesis Testing  Procedure for deciding whether the outcome of a study (results for a sample) support a particular theory or practical innovation (which is thought to apply to a population)

3. Core Logic of Hypothesis Testing  Considers the probability that the result of a study could have come about if the experimental procedure had no effect  If this probability is low, scenario of no effect is rejected and the theory behind the experimental procedure is supported

4. The Hypothesis Testing Process 1.Restate the question as a research hypothesis and a null hypothesis about the populations  Population 1  Population 2  Research hypothesis  Null hypothesis

5. The Hypothesis Testing Process 2.Determine the characteristics of the comparison distribution  Comparison distribution

6. The Hypothesis Testing Process 3.Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected  Cutoff sample score  Conventional levels of significance: p <.05, p <.01

7. The Hypothesis Testing Process 4.Determine your sample’s score on the comparison distribution 5.Decide whether to reject the null hypothesis

8. One-Tailed and Two-Tailed Hypothesis Tests  Directional hypotheses –One-tailed test  Nondirectional hypotheses –Two-tailed test

9. Determining Cutoff Points With Two-Tailed Tests  Divide up the significance between the two tails

10. Controversies and Limitations  Criticisms of basic logic of significance tests  Misuse of significance tests  Significance testing “... is easily misunderstood but that when applied with good judgment it can be an effective aid in the interpretation of experimental data” (Nickerson, 2000)

11. Hypothesis Tests in Research Articles  Reported with regard to specific statistical procedures  “Near significant trend”  Not significant, ns

12. Hypothesis Tests in Research Articles  Shown as asterisks in a table of results