OUTLINE FOR CHAPTER 8

Effect Size, Power, CIs, and Bonferroni

  1. The Seven-Step Version of Hypothesis Testing
    1. Introduction:
      1. A brief review of the simplest version of hypothesis testing
      2. The 7th step: After rejecting Ho, determining the degree to which Ho was wrong
      3. The difference between "statistical significance" and "practical significance"
    2. Two ways researchers can do Step #7
      1. They can compute a measure of "effect size"
      2. They can conduct a post hoc "power analysis"
  2. The Nine-Step Version of Hypothesis Testing
    1. A simple listing of the nine steps . . . with the 3 "new" steps located in positions 4, 5, and 6
    2. Step #4: Specification of the effect size (ES):
      1. ES: the point that separates cases where Ho is false by a small and trivial amount vs. cases where it's false by a big and noteworthy amount
      2. Two options for ES: "Raw" or "standardized" (and Cohen's "standards")
    3. Step #5: Specification of the desired level of "power":
      1. The notions of "statistical power" and a "beta error"
      2. Why researchers donšt set power at .999
    4. Step #6: Determination of the needed sample size:
      1. Computing n from a formula or looking up the needed n in a chart
      2. What to do if there is a fixed n
    5. The primary advantage of using the 9-step version of hypothesis testing
  3. Hypothesis Testing Using Confidence Intervals
    1. Using a confidence interval to test a null hypothesis about a single population
    2. Using a confidence interval to test a null hypothesis involving two populations
  4. Adjusting for an Inflated Type I Error Rate
    1. The notion of an "inflated Type I error rate"
    2. Why the Type I error rate becomes "inflated" if a fixed alpha is used with multiple tests
    3. The Bonferroni adjustment technique
    4. The experimentwise error rate
    5. The Dunn-Sidak modification
  5. A Few Cautions
    1. Two meaning of the term "effect size"
    2. "Small," "medium," and "large" effect sizes
    3. The simplistic nature of the 6-step version of hypothesis testing
    4. Inflated Type I error rates

Copyright © 2012

Schuyler W. Huck
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