Judge whether below statements are right or not 1.1) To examine the adequacy of the model, we usually detect the underlying model assumptions by examination of the standard summary statistics, such as tor F statistics, or R^2 1.2) Plotting the residuals against the corresponding values of each regressor variable is helpful in residual analysis. However, in the simple linear regression case, it is not necessary to plot residuals versus both fitted value and the regressor variable. The reason is that the fitted values are linear combinations of the regressor values, so the plots would only differ in the scale for the abscissa. 1.3)The ridge estimator of the regression coefficients in a multiple linear regression model is a nonlinear transformation of the least-square estimator. 1.4)For a qualitative variable with m levels involved in a multiple linear regression, one can represent it by m- 1 indicator variables