When the error variance is nonconstant,it is common to see the variation increases as the explanatory variable increases (you will see a "fan shape" in the scatterplot).There are two ways you can deal with this phenomenon.These are
A)the weighted least squares and a logarithmic transformation.
B)the partial F and a logarithmic transformation.
C)the weighted least squares and the partial F.
D)stepwise regression and the partial F.

Question

Quizplus · Accepted Answer

The correct methods to address nonconstant error variance, which often manifests as a "fan shape" in the scatterplot, are weighted least squares and a logarithmic transformation. Weighted least squares adjust the weights of data points to account for differences in variance, while a logarithmic transformation can stabilize variance across the range of data.

When the Error Variance Is Nonconstant,it Is Common to See