need help

Consider a logistic regression model, that is P(Y = 1[X = >) = exp(Bo + Bix) 1 + exp(Bo + BIZ) =1 -P(Y = 0|X = x). After fitting the regression, we predict the class as A = (x), which can be either 0 or 1. ~ 1. Justify that P(Y # j(x)) = E(Y - (x))2. 2 .Next, show that E[(Y - )?(X = x] = P(Y = 1/X = >)(1 -2/(x)) + 2(x) 3. Calculate the misclassification errors in the different cases (Hint: make a contingency table) and justify the following choices: . If P(Y = 1/X = x) > 0.5, we should have f(r) = 1. . If P(Y = 1 X = x)