Homoscedasticity is the condition that a collection of random variables has a common variance. In a regression model, the errors are homoscedastic when
 |
for every observation 
,
where 
denotes the predictor data. The constant-variance assumption
is used in the usual standard error formulas for
ordinary least squares fitting. Its failure
is heteroscedasticity.
