Tests on Three or More Means Using a One-Way ANOVA

  1. Introduction
    1. The versatility and popularity of ANOVA techniques
    2. The focus of this chapter: one-way ANOVAs
  2. The Purpose of a One-Way ANOVA
    1. The number of inference made
    2. The direction and focus of the inference
  3. The Distinction Between One-Way ANOVAs and Other Kinds of ANOVAs
    1. Synonyms for "one-way ANOVA"
    2. The number of independent variables (i.e., factors) and dependent variables
    3. The "between" vs. "within" nature of the independent variable
  4. The One-Way ANOVA's Null and Alternative Hypotheses
    1. Two ways to express the null hypothesis
    2. Using symbols to express the alternative hypothesis
  5. Presentation of Results
    1. Results of a single one-way ANOVA
      1. A typical ANOVA summary table
      2. Using df values
      3. Textual presentation of results
    2. Results of two or more one-way ANOVAs
      1. Presenting findings within a passage of text
      2. The null hypotheses when the same groups are compared on different dependent variables
    3. The Bonferroni adjustment technique
  6. Assumptions of a One-Way ANOVA
    1. The four main assumptions
    2. Checking on the normality and equal variance assumptions
    3. Four options when the assumptions seem untenable
    4. Independence and the "unit of analysis"
  7. Statistical Significance Versus Practical Significance
    1. Two options
    2. Do researchers typically worry about practical significance?
    3. Criteria when using standardized effect sizes
  8. Cautions
    1. Significant and nonsignificant results from one-way ANOVAs
    2. Confidence intervals
    3. Other things to keep in mind
  9. A Final Comment
    1. The single most important thing in any one-way ANOVA
    2. A one-way ANOVA that didn't need to be conducted (because its outcome was known before the analysis began)


Copyright © 2012

Schuyler W. Huck
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