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A00-240 Exam Dumps : SAS Statistical Business Analysis SAS9: Regression and Model

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SAS Statistical Business Analysis SAS9: Regression and Model Questions and Answers

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Question 1

A predictive model uses a data set that has several variables with missing values.

What two problems can arise with this model? (Choose two.)

Options:

A.

The model will likely be overfit.

B.

There will be a high rate of collinearity among input variables.

C.

Complete case analysis means that fewer observations will be used in the model building process.

D.

New cases with missing values on input variables cannot be scored without extra data processing.

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Question 2

An analyst knows that the categorical predictor, zip_code, is an important predictor of a binary target. However, zip_code has too many levels to be a feasible predictor in a model. The analyst uses PROC CLUSTER to implement Greenacre's method to reduce the number of categorical levels.

What is the correct application of Greenacre's method in this situation?

Options:

A.

Clustering the levels using the target proportion for each zip_code as input.

B.

Clustering the levels using the zip_code values as input.

C.

Clustering the levels using the number of cases in each zip_code as input.

D.

Clustering the levels using dummy coded zip_code levels as inputs.

Question 3

Refer to the confusion matrix:

Calculate the sensitivity. (0 - negative outcome, 1 - positive outcome)

Click the calculator button to display a calculator if needed.

Options:

A.

25/48

B.

58/102

C.

25/B9

D.

58/81

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