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Discuss the following statements and explain why they are true or false: a) Increasing the number of predictor variables will never decrease the R2...

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I need help in answering these statistics regression 2 questions (see attached sheets)

II. Discuss the following statements and explain why they are true or false: a) Increasing the number of predictor variables will never decrease the R 2 b) Multicollinearity affects the interpretation of the regression coefficients c) The variance inflation factor of j β ˆ depends on the R 2 of the regression of the response variable Y on the regressor variable X j d) A high leverage point is always highly influential e) Standardized residuals are always smaller than the ordinary residuals. III. Indicate whether the following statements are true or false a) A Durbin-Watson statistic of zero indicates that all regressors are insignificant in predicting the response variable b) If a qualitative X variable has two levels/classes, then defining two indicator variables will make the X’X matrix invertible c) If the variance of the error term is proportional to X 2 , ie, Var( ε )=kX 2 , the appropriate weights are w=k/X 2 for performing weighted least squares. d) Ridge regression estimate is a biased estimator with a smaller MSE than the least squares estimate.

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II. Discuss the following statements and explain why they are true or false: a) Increasing the number of predictor variables will never decrease the R 2
False, because if we increase the number of...

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