The article discusses how repeated-measures analysis of variance (ANOVA) is used to compare different treatment conditions within the same group of participants. This method helps to determine if there are significant differences in population means across the treatment levels. By using formulas and computational steps, researchers can separate individual differences from experimental error in their analysis. If the null hypothesis is rejected in designs with multiple treatment levels, further comparisons are needed to identify where the differences lie.