Shown below is Minitab output from a logistic regression analysis to develop a model to predict whether a shopper in a mall store will purchase something by the number of miles the shopper drives to get to the mall store. The original data were coded as 1 if the shopper purchases something and 0 if they do not. Study the output and determine the model.

Discuss the strength or lack of strength of the model and the predictor. Use the output to compute the predicted probability that a person would purchase something if he/she drives 5 miles to get to the store. Now calculate the probabilities for 4 miles, 3 miles, 2 miles, and 1 mile. What happens to the probability over thesevalues?

Variable Value Count Buy? 65 (Event) Total 120 Logistic Regression Table Odds 95% CI Coef SE Coef 3.94828 0.736737 1.36988 0.255838 P Ratio Lower Upper Predictor Constant Miles to Store 5.36 0.000 5.35 0.000 3.93 2.38 6.50 Log-Likelihood32.492 Test that all slopes are zero: G = 100.537, DF = 1, P-value = 0.000