Homogeneity of variance ( homoscedasticity) is an important assumption shared by many parametric statistical methods. This assumption requires that that the variance within each population should be equal for all populations (two ore more, depending on the method). For example, this assumption is used in two-sample t-test and ANOVA. If the variances are not homogeneous, they are said to be heterogeneous. If this is the case we say that the underlying populations, or random variables, are heteroscedastic (sometimes spelled as heteroskedastic).