Introduction to One-Way ANOVA

• One-Way ANOVA is a statistical test used to compare means of three or more groups.

  • It determines if there is a significant difference between the groups.

Assumptions of One-Way ANOVA

• Independence: Observations are independent of each other.

• Normality: Residuals are normally distributed.

• Homogeneity of Variance: Variances are equal across groups.

One-Way ANOVA

Trivia: One assumption NOT required for One-Way ANOVA is Equal sample sizes. It only requires Independence, Normality, and Homogeneity of Variance.

Unlocking One-Way ANOVA

• Hypothesis Testing: Explore the differences between multiple groups

  • Null (No difference) vs. Alternative (At least one group differs)

• One-Way ANOVA: Determine if means of groups are significantly different

• Assumptions: Normality, Homogeneity of Variance, Independence

• Interpretation: F-statistic, p-value, Post-hoc tests

Homogeneity of Variance

• If HOV is greater than .05 (non-significant), then the assumption of homogeneity of variance is met. Therefore, it is assumed that the sample sizes have equal variances.

• If HOV is less than .05 (significant), then the assumption is not met. There are not equal variances between the sample sizes.

Post Hoc Tests: Tukey and Dunnett's T3

• Tukey and Dunnett's 3 are Post-Hoc tests that are used when the ANOVA test is significant (p < .05).

• Tukey is used when HOV is non-significant (p > .05)

• Dunnett's is used when HOV is significant (p < .05)