One of the assumptions in linear regression using the ordinary least square (OLS) method is that there is no strong correlation between independent variables. To get the Best Linear Unbiased Estimator in linear regression with ≥ 2 independent variables, you must be fulfilled the non-multicollinearity assumption.
The objective of the heteroscedasticity test is to determine whether the variance of residuals is constant. One of the assumption tests in linear regression using the ordinary least square (OLS) method is that the variance of residuals is constant.
The normality test is one of the assumption tests in linear regression using the ordinary least square (OLS) method. The normality test is intended to determine whether the residuals are normally distributed or not.
