In statistics, a sequence or a vector of random variables is homoscedastic if all random variables in the sequence or vector have the same finite variance. The converse is called heteroscedasticity. The assumption of homoscedasticity simplifies mathematical and computational treatment and may lead to good estimation results (e.g. in data mining) even if the assumption is not true.

(In Britain, it is sometimes spelled homoskedastic. It is an exception to the rule that American spellings are usually more faithful to the etymologies than British spellings.)