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11: One-Way Analysis of Variance

  • Page ID
    42061
    • Linda R. Cote, Rupa G. Gordon, Chrislyn E. Randell, Judy Schmitt, and Helena Marvin
    • University of Missouri System

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    • 11.1: Sources of Variability
      This page discusses ANOVA (Analysis of Variance), which tests for differences in means across two or more groups and addresses variability by distinguishing between systematic and random factors. It explains the calculation of sums of squares for within-groups and between-groups variance, organized in an ANOVA table detailing sources of variability, degrees of freedom, and F values.
    • 11.2: Hypothesis Testing with Analysis of Variance
      This page explores formal hypotheses in ANOVA, covering the null hypothesis (H0: no differences in group means) and the alternative hypothesis (HA: at least one mean differs). An example of a one-way ANOVA shows significant differences in job skills test scores among three education groups, with an F statistic of 36.86, leading to H0 rejection and a large effect size (η² = 0.73).
    • 11.3: ANOVA Post-Hoc Tests
      This page discusses post hoc tests used to identify specific group differences after significant findings. It highlights the Bonferroni test for Type I error control, Tukey’s HSD for comparisons with confidence intervals, and the Scheffé test as a conservative option. Although various post hoc tests exist, they typically produce similar outcomes, and careful interpretation of confidence intervals is crucial for understanding group differences.


    This page titled 11: One-Way Analysis of Variance is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Linda R. Cote, Rupa G. Gordon, Chrislyn E. Randell, Judy Schmitt, and Helena Marvin via source content that was edited to the style and standards of the LibreTexts platform.