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Heteroskedasticity

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Multiplying an estimating equation by a correcting factor to correct heteroskedasticity may cause extra correlation to enter the model, which raises the R^2. This renders our ultimate regression results meaningless. True or false, or uncertain? Please provide an explanation.

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https://brainmass.com/economics/regression/heteroskedasticity-problem-115452

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The answer is false. A regression model is useless until all the regression assumptions are satisfied. So a regression model where Heteroskedasticity is not satisfied is a useless model. We must make necessary correcting adjustments to remove Heteroskedasticity.

Multiplying a regression ...

Solution Summary

Explains why a regression model where Heteroskedasticity is not satisfied is a useless model.

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Heteroskedasticity Residual Plots

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