For ANOVA,when the null hypothesis is true,the F-ratio is balanced so that the numerator and the denominator are both measuring the same sources of variance.

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When the null hypothesis is true, the F-ratio represents the ratio of the variance between the groups to the variance within the groups. If the null hypothesis is true, there should be no systematic differences between the groups, so the numerator (between-group variance) and the denominator (within-group variance) should be relatively equal. This results in a balanced F-ratio with a value close to 1.

For ANOVA,when the Null Hypothesis Is True,the F-Ratio Is Balanced