Question 4 (10 points) The output of a linear regression model, which shows the relationship between Lewis University men's basketball performance score in a tournament and their players' height and weight, is as follows. SUMMARY OUTPUT Regression Statistics Multiple R 0.749506109 R Square 0.561759407 Adjusted R Square 0.51020169 Standard Error 0.138710834 Observations ANOVA df SS MS Significance F Regression 0.419283178 0.209641589 10.89573864 0.000900652 Residual 0.327091822 0.019240695 Total 0.746375 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0%% Upper 95.0% Intercept 1.366505227 0.437591956 -3.122784159 0.006194451 -2.289743552 -0.443266902 -2.289743552 -0.443266902 Height 0.303338894 0.09397419 3.227895803 3 0.0049417 0.105070684 0.501607104 0.105070684 0.501607104 Weight 0.000760975 0.001713889 0.444004676 0.662639055 -0.002855015 0.004376964 -0.002855015 0.004376964 1- Is this overall a valid model? (a = 0.05) 2- How much variance is explained in this model? 3- Write the regression equation. 4- How do you interpret the finding? Question 5 (10 points) The output of a logistic regression model, which shows the relationship between a pass or fail of business analytics students on the final exam and students' attention during the lecture in the classroom, showing up late in the class, hours of studying each week, and their height is as follows. Logistic regression Number of obs 144 11 LR chi2(4) 65.73 Prob > chi2 0000 .0 Log likelihood = -66.947876 Pseudo R2 0.3293 PassFail | Coef. Odds Ratio Z P> /z| [95% Conf. Interval] Attention . 023589 1. 023869 2.13 0.033 . 0018429 . 045335 late . 0443886 . 9565821 -3.15 0. 002 . 0719842 . 016793 Studying . 2266635 1.254408 4.25 0.000 1220177 . 3313093 Height . 2694518 1. 309247 0.93 0.353 -. 2992337 . 8381373 1- Write the logistic equation. 2- Interpret the estimated coefficients of each variable. 3- Which variables are significant at a 5% statistical level? 4- Interpret the odds ratios of pass/fail for each variable