Salmons Stores operates a national chain of women's apparel stores. Five thousand copies of an expensive four-color sales catalog have been printed, and each catalog includes a coupon that provides a $50 discount on purchases of $200 or more. Salmons would like to send the catalogs only to customers who have the highest probability of using the coupon. The data table below contains data from an earlier promotional campaign. For each of 1,000 Salmons customers, three variables are tracked: last year's total spending at Salmons, whether they have a Salmons store credit card, and whether they used the promotional coupon they were sent.(a) Create a standard partition of the data with all the tracked variables and 50% of observations in the training set, 30% in the validation set, and 20% in the test set. Use logistic regression to classify observations as a promotion-responder or not by using Spending and Card as input variables and Coupon as the output variable. Perform Variable Selection with the best subsets procedure with the number of best subsets equal to two.(b) Evaluate the logistic regression models based on their classification error. Recommend a final model and express the model as a mathematical equation relating the output variable to the input variables. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a sign before the blank. (Example: -300)Customer Spending Card Coupon1 2291 1 02 3215 1 03 2135 1 04 3924 0 05 2528 1 06 2473 0 17 2384 0 08 7076 0 09 1182 1 110 3345 0 011 2140 1 012 3255 0 113 1512 0 014 2148 0 115 6737 0 016 6486 0 017 1307 0 018 3470 1 019 2936 0 020 6404 0 121 2229 0 022 2933 0 023 2118 0 024 2050 0 025 4998 0 126 1394 0 027 3993 1 128 2059 0 129 1677 0 0