Question 1
Refer to the exhibit:
An analyst examined logistic regression models for predicting whether a customer would make a purchase.
The ROC curve displayed summarizes the models. Using the selected model and the analyst's decision rule,
25% of the customers who did not make a purchase are incorrectly classified as purchasers.
What can be concluded from the graph?
Question 2
Refer to the exhibit.
Based on the control plot, which conclusion is justified regarding the means of the response?
Question 3
Suppose training data are oversampled in the event group to make the number of events and non-events
roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the
variable name PE. A decision rule considered is, "Classify data as an event if probability is greater than
0.5." Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0
No event).
The following SAS program was used.
What does this program calculate?
Question 4
Within PROC GLM, the interaction between the two categorical predictors, Income and Gender, was shown to be significant. An item store was saved from the GLM analysis.
Which statement from PROC PLM would test the significance of Gender within each level of Income and adjust for multiple tests?
sliceby Gender / adjust=tukey;
Question 5
Assume a $10 cost for soliciting a non-responder and a $200 profit for soliciting a responder. The logistic regression model gives a probability score named P_R on a SAS data set called VALID. The VALID data set contains the responder variable Pinch, a 1/0 variable coded as 1 for responder. Customers will be solicited when their probability score is more than 0.05.
Which SAS program computes the profit for each customer in the data set VALID?