The existence of an outlier in the data causes heteroscedasticity. Heteroscedasticity can also be produced when variables are omitted from the model. Heteroscedasticity implies just two hypotheses: the null hypothesis and the alternate hypothesis. When applying the White test, Breusch-Pagan, or Cook-Weisberg tests to check for heteroscedasticity, the null hypothesis is true if the variances of the errors are equal. An alternate hypothesis occurs when the variances of the errors are not identical.