Consider a binary response variable y and a predictor variable x. 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 Intercept LPM Logistic -0.67 -6.90 (0.02) (0.06) Coefficients Intercept Slope 0.07 (0.03) 0.19 (0.06) a. Test for the significance of the intercept and the slope coefficients at the 5% level in both models. LPM Logistic b. What is the predicted probability implied by the linear probability model for x = 20 and x = 357 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 %).
Consider a binary response variable y and a predictor variable x. 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 Intercept LPM Logistic -0.67 -6.90 (0.02) (0.06) Coefficients Intercept Slope 0.07 (0.03) 0.19 (0.06) a. Test for the significance of the intercept and the slope coefficients at the 5% level in both models. LPM Logistic b. What is the predicted probability implied by the linear probability model for x = 20 and x = 357 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 %).
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 8E
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