The Brown-Forsythe test and the Barlett test. Prism can test this assumption with two tests. Are the residuals clustered or heteroscedastic? ANOVA assumes each sample was randomly drawn from populations with the same standard deviation.ANOVA assumes a Gaussian distribution of residuals, and this graph lets you check that assumption. The Y axis is the predicted residual, computed from the percentile of the residual (among all residuals) and assuming sampling from a Gaussian distribution. The Y axis is the absolute value of the residual.This lets you check whether larger values are associated with bigger residuals (large absolute value). The X axis is the predicted value (or fitted value), the mean of the replicates of the data (but see below for repeated measures). This lets you spot residuals that are much larger or smaller than the rest. Prism can make three kinds of residual plots. A residual plot helps you assess this assumption. One of the assumptions of ANOVA is that the residuals from that model are sampled from a Gaussian distribution. But ANOVA is really regression in disguise. Many scientists thing of residual as values that are obtained with regression. Prism 8 introduced the ability to plot residual plots with ANOVA, provided that you entered raw data and not averaged data as mean, n and SD or SEM.