Eliminating Homoscedasticity from the data set before linear regression

@Prateek123 wrote:

Hello everyone,

There are several assumptions that we take before applying linear regression.
These include :
1) Eliminating multicollinearity.
2) Normalization of the variables
3) Eliminating homoscedasticity that is the correlation between error terms and independent variables.

For the third point, how do we treat a data set that has homoscedasticity in it? And how significant a change do we observe by doing so in linear regression?

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