Homoscedasticity versus heteroscedasticity
Homoscedasticity can be also called homogeneity of variance, because it is about a situation, when the sequence or vector of rando variable have the same finite variance. And as we probably know already – variance measures how far a set of numbers is spread out. The complementary notion is called heteroscedasticity, to sum up, it means that:
- In statistics, a sequence or a vector of random variables is homoscedastic /ˌhoʊmoʊskəˈdæstɪk/ if all random variables in the sequence or vector have the same finite variance.
- A collection of random variables is heteroscedastic if there are sub-populations that have different variabilities from others.