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  • Exam Name: SAS Statistical Business Analysis SAS9: Regression and Model
  • Last Update: 17-Sep-2024
  • Questions and Answers: 99
  • Single Choice: 87 Q&A's
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A00-240 Questions and Answers

Question # 1

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?

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 # 2

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:

A00-240 question answer

At Step 9 number of at bats (nAtBat) was removed from the model.

Why was it removed?

A.

Removing nAtBat had the largest effect on the parameter estimate of nHits.

B.

The p-Value for nAtBat was largest.

C.

Removing nAtBat yielded the largest improvement to SBC.

D.

The p-Value for nAtBat was smallest.

Question # 3

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:

  • Target variable Respond (0, 1)
  • Continuous predictor Income
  • Categorical predictor Homeowner(Y, N)

Which SAS program performs this analysis?

A00-240 question answer

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question # 4

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?

A.

All parameter estimates are biased.

B.

Only the intercept estimate is biased.

C.

Only the non-intercept parameter estimates are biased.

D.

Sensitivity estimates are biased.

Question # 5

Which characteristic of Studentized residuals indicate potential outliers?

A.

Only studentized residuals greater than negative two

B.

Only studentized residuals less than negative two and greater than two

C.

Only studentized residuals greater than two

D.

Only studentized residuals less than two and greater than negative two

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