Consider a binary response variable y and two predictor variables x₁ and x₂. The following table contains the parameter estimates of the linear probability model (LPM) and the logistic regression model, with the associated p-values shown in parentheses.

Variable	LPM	Logistic
Intercept	?0.50	?1.90
(0.02)	(0.06)
x1	0.26	0.99
(0.06)	(0.06)
x2	?0.06	?0.30
(0.01)	(0.04)

Variable LPM Logistic -0.50 -1. 90 Intercept (0.02) (0. 06) 0 . 26 0. 99 X1 (0. 06) (0. 06) -0 . 06 -0. 30 X2 (0. 01) (0. 04) ces a. At the 5% significance level, comment on the significance of the variables for both models. Variable LPM Logistic X1 X2a. At the 5% significance level, comment on the significance of the variables for both models. Variable LPM Logistic X1 X2 b. What is the predicted probability implied by the linear probability model for x1 = 8 with x2 equal to 10 and 25? Note: Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and 1 (not in %). X1 = 8, X2 = 10 X1 = 8, X2 = 25c. What is the predicted probability implied by the logistic model for x1 = 8 with X2 equal to 10 and 25? Note: Round intermediate calculations to at least 4 decimal places and final answers to 2 decimal places. Report the probability between 0 and 1 (not in %). X1=8,X2=10 X1=8,X2=25