Homocadasticity

In statistics, a sequence or a vector of random variables is homoscedastic (pronounced /ˌhoʊmoʊskəˈdæstɪk/) if all random variables in the sequence or vector have the same finite variance. This is also known as homogeneity of variance. The complementary notion is called heteroscedasticity. The spellings homoskedasticity and heteroskedasticity are also used frequently.

The assumption of homoscedasticity simplifies mathematical and computational treatment. Serious violations in homoscedasticity (assuming a distribution of data is homoscedastic when in actuality it is heteroscedastic (pronounced /ˌhɛtəroʊskəˈdæstɪk/) may result in overestimating the goodness of fit as measured by the Pearson coefficient.