# Homoscedasticity

Plot with random data showing homoscedasticity.

In statistics, a sequence or a vector of random variables is homoscedastic Template:IPAc-en 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 frequently used.[1]

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 Template:IPAc-en) may result in overestimating the goodness of fit as measured by the Pearson coefficient.

## References

1. For the Greek etymology of the term, see {{#invoke:Citation/CS1|citation |CitationClass=journal }}
2. Hamsici, Onur C.; Martinez, Aleix M. (2007) "Spherical-Homoscedastic Distributions: The Equivalency of Spherical and Normal Distributions in Classification", Journal of Machine Learning Research, 8, 1583-1623