1. What is the meaning of "ANOVA"?
2. How many populations does t-test statistic compare?
3. How many populations does ANOVA compare?
4. ANOVA doesn't give us all the information we need to interpret the differences between groups. What information ANOVA provides?
5. What do you need to do beyond ANOVA to interpret differences between the groups?
6. What kind of variables do you use with ANOVA? How many levels for these variables can have?
7. When you're running an ANOVA we no longer have t-test or distribution, instead we use the _______ test and the _______distribution.
8. Distinguish between the null hypothesis and the research hypothesis.
9. When does the researcher decides to reject the null hypothesis?
10. What is meant by statistical significance?
11. What factors are most important in determining whether obtained results will be significant?
12. Distinguish between Type I and a Type II error.
13. What factors are involved in choosing a significance level?
14. What influences the probability of a Type II error?
15. What is the difference between statistical significance and practical significance?
16. Discuss the reasons why a researcher might obtain no significant results.