If within-groups variance is large relative to between-groups variance, then there is increased probability of:

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When within-groups variance is large relative to between-groups variance, it indicates that the differences within each group are greater than the differences between the groups. This scenario makes it harder to detect a true effect or difference between groups, thereby increasing the probability of making a Type II error, which occurs when the null hypothesis is falsely accepted (failing to reject the null hypothesis when it is false).

If Within-Groups Variance Is Large Relative to Between-Groups Variance, Then