Using Purchases and Card, perform a linear discriminate analysis of the coupon redemption data. (Round your answers to 4 decimal places.) 1. The probability for customer 41 who will redeem the coupon is? 2. The probability for customer 42 who will not redeem the coupon is? UpGrade Purchases PlatProfile 0 27.94 0 0 5.34 0 0 41.83 1 1 10.52 1 1 127.8 1 1 18.44 0 1 79.32 1 0 7.62 0 0 46.61 1 0 16.7 0 0 74.32 0 0 5.73 0 1 132.97 1 1 18.51 0 1 72.9 1 0 1.79 0 1 114.72 1 0 12.57 1 0 76.85 1 1 19.24 1 0 35.18 0 1 18.49 1 1 111.59 1 0 10.66 0 0 104.1 0 1 20.93 1 0 63.03 0 0 8.58 0 0 135.15 0 1 13.03 1 1 91.3 1 1 13.62 1 1 148.24 1 0 7.7 0 1 108.16 1 1 16.7 1 0 92.68 0 0 11.47 0 0 112.2 0 0 9.41 0 43.97 1 52.48 0
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To perform a Linear Discriminant Analysis (LDA) on the given coupon redemption data, we need to follow these steps: Show more…
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Salmon 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. Salmon would like to send the catalogs only to customers who have the highest probability of using the coupon. The DATA file Salmon contains data from an earlier promotional campaign. For each of 1,000 Salmon customers, three variables are tracked: last year's total spending at Salmon (Spending), whether they have a Salmon store credit card (Card), and whether they used the promotional coupon they were sent (Coupon). Apply 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. Refer to the Appendix for instructions on how to perform logistic regression using the Analytic Solver Platform. In the Parameters tab, Partition Data and Use partition variable named Partition, and perform Feature Selection with the Best Subsets method. In the Scoring tab, generate a Detailed Report and Lift Charts on the test data. A) 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) Value = ____ + ____ Spending + _____ Card b) What is the area under the ROC curve on the test set? If required, round your answer to three decimal places. _______ To achieve a sensitivity of at least 0.80, how much Class 0 error rate must be tolerated? If required, round your answer to two decimal places. _____ C) For the model selected in part (a), interpret the meaning of the first-decile lift in the decile-wise lift chart on the test set. Explain:_____
Shyam P.
The marketing department for a credit card company wants to determine which of its existing standard credit card holders should be targeted for a campaign to convince existing cardholders to upgrade to the company's premium card for a nominal annual fee. They have access to data from a sample of 30 cardholders who were contacted during last year's campaign that indicates whether the cardholder upgraded to a premium card (0 equals no, 1 equals yes). The results for their logistic regression model are -7.118 + 0.13271X1 + 2.593X2, where X1 is the total amount of credit card purchases (in thousands of dollars) in the prior year and X2 is whether the cardholder ordered additional credit cards, at extra cost, for other members of the household (0 equals no, 1 equals yes). a. Predict the probability that a cardholder who charged $34,000 last year and does not have any additional credit cards for members of the household will purchase the premium card during the market campaign.
Madhur L.
The table provides estimates of the probability of using the coupon in the Simmons Stores catalog promotion. A different value is obtained for each combination of values for the independent variables. Annual Spending $1,000 $2,000 $3,000 $4,000 $5,000 $6,000 $7,000 Credit Card Yes 0.3307 0.4102 0.4948 0.5796 0.6599 0.7320 0.7936 No 0.1414 0.1881 0.2460 0.3148 0.3927 0.4765 0.5617 These values were obtained from a logistic regression equation where x1 = annual spending at Simmons Stores ($1,000s) x2 = 0 if the customer does not have a Simmons credit card 1 if the customer has a Simmons credit card y = 0 if the customer did not use the coupon 1 if the customer used the coupon. (a) Compute the odds in favor of using the coupon for a customer with annual spending of $4,000 who does not have a Simmons credit card (x1 = 4, x2 = 0). (Round your answer to four decimal places.) (b) Use the information in the table and in part (a) to compute the odds ratio for the Simmons credit card variable x2 = 0, holding annual spending constant at x1 = 4. (Round your answer to two decimal places.) (c) The odds ratio for the Simmons credit card variable computed using the information in the $2,000 column of the table was 3.00 (rounded to two decimal places). Did you get the same value for the odds ratio in part (b)? Both rounded to two decimal places, the odds ratio for x2 computed holding annual spending constant at $4,000 ---Select--- (is, is not) the same as the odds ratio for x2 computed holding annual spending constant at $2,000. This shows that the odds ratio for x2 ---Select--- (is, is not) independent of the value of x1.
Samriddhi S.
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