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Suppose training data are oversampled in the event group to make the number of events and nonevents 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? A. Depth B. Sensitivity C. Specificity D. Positive predictive value
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tailor Says :  published on : (12/9/2013 11:37:42 AM)  B 


Refer to the exhibit: The plots represent two models, A and B, being fit to the same two data sets, training and validation. Model A is 90.5% accurate at distinguishing blue from red on the training data and 75.5% accurate at doing the same on validation data. Model B is 83% accurate at distinguishing blue from red on the training data and 78.3% accurate at doing the same on the validation data. Which of the two models should be selected and why? A. Model A. It is more complex with a higher accuracy than model B on training data. B. Model A. It performs better on the boundary for the training data. C. Model B. It is more complex with a higher accuracy than model A on validation data. D. Model B. It is simpler with a higher accuracy than model A on validation data.
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tailor Says :  published on : (12/9/2013 11:38:10 AM)  D 


Assume a $10 cost for soliciting a nonresponder 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? A. Option A B. Option B C. Option C D. Option D
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