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How to determine violation of assumptions in linear regression model?

Violation of linearity can be determined if the plot developed forms a ‘bowed pattern’. The only way to fix this violation is to include nonlinear transformation to the independent and dependent variable. Violation of independence can be determined to check for correlations near the first lags and in the vicinity of the seasonal period.

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By Veena Answered 6 years ago

By Raghu Answered 6 years ago

Use a scatter plot or IF factor to determine the violation of multicollinearity. If VIF value is less than 4 then there is no multicollinearity.
If VIF is greater than 10, then there is multicollinearity. The best method to overcome the violation is to remove the VIF (only 1 among 2). Alternatively,
you can use partial least square regression.

By Anusha Answered 6 years ago

Neethi, use the normal probability plot to determine the violation of normality. If the plot represents an S shape,
then there are too many errors on both sides of the plot. If the plot represents bow-shaped, then the residuals have excess errors.
And to fix this, then implement nonlinear transformation.

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