A confusion matrix is created for data that were oversampled due to a rare target.
What values are not affected by this oversampling?
Show answer and explanation
Correct answer: D
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A confusion matrix is created for data that were oversampled due to a rare target.
What values are not affected by this oversampling?
Correct answer: D
FILL BLANK
Refer to the REG procedure output:

How many observations are used in the analysis? Enter your numeric answer in the space below.
Accepted answer: 100
Refer to the exhibit.

Based on the control plot, which conclusion is justified regarding the means of the response?
Correct answer: C
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?
Correct answer: C
One common approach for predicting rare events in the LOGISTIC procedure is to build a model that disproportionately over-re presents those cases with an event occurring (e.g. a 50-50 event/non-event split).
What problem does this present?
Correct answer: B
PROC GLMSELECT was used for building a model predicting the natural log of a baseball player's salary from certain performance and longevity statistics. The model used backward elimination using SBC as its selection criterion. The sequence of steps is summarized in the graphic shown below:

At Step 9 number of at bats (nAtBat) was removed from the model.
Why was it removed?
Correct answer: B
A marketing campaign will send brochures describing an expensive product to a set of customers. The cost for mailing and production per customer is $50. The company makes $500 revenue for each sale.
What is the profit matrix for a typical person in the population?

Correct answer: C
An analyst knows that the categorical predictor, storeId, is an important predictor of the target.
However, store_Id has too many levels to be a feasible predictor in the model. The analyst wants to combine stores and treat them as members of the same class level.
What are the two most effective ways to address the problem? (Choose two.)
Correct answers: B, C
A marketing manager attempts to determine those customers most likely to purchase additional products as the result of a nation-wide marketing campaign.
The manager possesses a historical dataset (CAMPAIGN) of a similar campaign from last year.
It has the following characteristics:
1. Target variable Respond (0, 1)
2. Continuous predictor Income
3. Categorical predictor Homeowner(Y, N)
Which SAS program performs this analysis?

Correct answer: A
Refer to the following odds ratio table:

What is a correct interpretation of the estimate?
Correct answer: B