Question 1 {3 points) mu Suppose a multiple regression model is fitted into a variable called model. Which Python method below returns residuals for a data set based on a multiple regression model? Select one. 0 model.residvalues O model.resid O model.residuals O model.residualsvalues Question 2 (3 points) ) Listen The ols() method in statsmodels module is used to fit a multiple regression model using "Exam4" as the response variable and "Exam1", "Exam2", and "Exam3" as predictor variables. The output is shown below. A text version is available. What is the correct regression equation based on this output and what is the coefficient of determination? Select one. OLS Regression Results Dep. Variable: Exam4 R-squared: 0. 178 Mode : OLS Adj . R-squared: 0. 125 Method: Least Squares F-statistic: 3. 329 Date: Fri, 16 Aug 2019 Prob (F-statistic) : 0. 0276 Time : 12 : 38: 46 Log-Likelihood: 169.85 No. observations : 50 AIC: 347.7 Df Residuals: 46 BIC: 355.4 of Model: Covariance Type: nonrobust coef std err P> It [0. 025 0. 975] --- Intercept 46. 2612 10.969 4. 217 0.000 24. 181 68 . 341 Exam1 0. 1742 0. 120 1.453 0. 153 -0. 067 0. 416 Exam2 0. 1462 0. 078 1.873 0. 067 -0. 011 0. 303 Exam3 0. 0575 0. 053 1. 085 0. 284 -0. 049 0 . 164 Omni bus : 0. 886 Durbin-Watson: 1. 530 Prob (Omni bus) : 0. 642 Jar que-Bera (JB) : 0. 738 Skew: 0. 290 Prob (JB) : 0. 691 Kurtosis : 2. 868 Cond. No. 1. 41e+03 Exam4 = 46.2612 + 0.1742 Exam1 + 0.1462 Exam2 + 0.0575 Exam3 coefficient of determination = 0.178 Exam4 = 10.969 + 0.120 Exam1 + 0.078 Exam2 + 0.053 Exam3 coefficient of determination = 3.329 Exam4 = 10.969 + 0.120 Exam1 + 0.078 Exam2 + 0.053 Exam3 coefficient of determination = 0.178 Exam4 = 46.2612 + 0.1742 Exam1 + 0.1462 Exam2 + 0.0575 Exam3 coefficient of determination = 3.329Question 3 {3 points) mu What is a fitted value for a multiple regression model and the data that is used to create it? Select one. 0 It is a statistic that explains the relationship between response and predictor variables. 0 It is the difference between the actual value of the response variable and the corresponding predicted value {regression error) using the multiple regression model. 0 It is the predicted value of the response variable using the multiple regression model. 0 It is a statistic that is used to evaluate the significance of the multiple regression model. Question 4 (3 points) ) Listen Which of the following correctly shows the general form of a multiple regression model? Select one. OY = Bot BIX1 O B , X 1 = Y + Bot BzX2 + ... + BnXn O ? = Bot BIX, + B2X2 + ...+ BnXn OB, X 1 = PQuestion 5 {3 points) 3- '5 Listen : Which of the following choices correctly identifies the following Q-Q plots for the normality of residuals assumption? Select one. 0 Graph B shows residuals with a distribution that more closely approximates a Normal distribution than Graph A. 0 Graph A shows residuals with a distribution that more closely approximates a Normal distribution than Graph B. 0 Both graphs show residuals with a distribution that is not Normal. 0 Graphs A and B both show residuals with distributions that closely approximate a Normal distribution