• Homoscedasticity occurs when the variance of the error term in the regression model is constant.

  • If the variance of the error term is homoscedastic, the model is well defined. If there is too much variance, the model may not be correctly defined.
  • Adding additional predictor variables can help explain the performance of the dependent variable.
  • Conversely, heteroskedasticity occurs when the variance of the error term is not constant.