30th Oct 2023

ANOVA, or Analysis of Variance, is a statistical method used to compare the average values of three or more sets and determine if there are significant differences in their means. To apply ANOVA effectively, certain prerequisites must be met: the observations within each group should be independent, the dependent variable should exhibit a degree of normal distribution, variances across groups should be relatively consistent, random selection should be used for sampling, the dependent variable should be continuous, and outliers should be identified and managed to avoid skewing the results.

ANOVA is a preferred choice when dealing with multiple groups, as it minimizes the risk of Type I errors that can occur when conducting multiple t-tests for each group combination. A significant ANOVA result suggests differences in group means but doesn’t specify which groups differ. Post-hoc tests like Tukey’s HSD or Bonferroni are commonly used to identify the specific groups with significant differences.