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Read online free dumps for SAS Institute- A00-250

Here you can read online questions and answers for SAS Institute Exam A00-250 (SAS Platform Administration for SAS9 ) 100% free...

Question ID 9013

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.)

Option A

Eliminate store_id as a predictor in the model because it has too many levels to be feasible.

Option B

Cluster by using Greenacre's method to combine stores that are similar.

Option C

Use subject matter expertise to combine stores that are similar.Use subject matter expertise to combine stores that

Option D

Randomly combine the stores into five groups to keep the stochastic variation among the
observations intact.

Correct Answer BC
Description
Update Date and Time 2017-08-11 12:48:22

Question ID 9014

Including redundant input variables in a regression model can:

Option A

Stabilize parameter estimates and increase the risk of overfitting.

Option B

Destabilize parameter estimates and increase the risk of overfitting.

Option C

Stabilize parameter estimates and decrease the risk of overfitting.

Option D

Destabilize parameter estimates and decrease the risk of overfitting.

Correct Answer B
Description
Update Date and Time 2017-08-11 12:50:07