In regression analysis, the Exam dataset is analysed in R and its output is as follows. Call: glm(formula = result ~ test + paper, family = "binomial", data = Exam) Deviance Residuals: Min 1Q Median 3Q Max -2.40363 -0.43696 -0.07681 0.44613 2.08213 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -15.52439 2.35453 -6.593 4.30e-11 *** test 0.16269 0.02443 6.658 2.77e-11 *** paper 0.06139 0.01417 4.332 1.48e-05 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 221.41 on 159 degrees of freedom Residual deviance: 102.86 on 157 degrees of freedom AIC: 108.86 Number of Fisher Scoring iterations: 6 a) Using this output, specify the response and independent variables. (5) b) Based on the output, which type of GLM is proposed for this analysis. (5) c) What is the link function for your proposed GLM model. (5) d) Specify the significant independent variables on the response variable at the level of = 0.05. (5) e) Find the 95% confidence interval for the intercept (0). (5) f) Using the output, find the optimal predictive model for the response variable.