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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

Question 1

An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation, and test sets to perform honest assessment during the model building process.

What is the purpose of the training data set?

Options:

A.

To provide an unbiased measure of assessment for the final model.

B.

To compare models and select and fine-tune the final model.

C.

To reduce total sample size to make computations more efficient.

D.

To build the predictive models.

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Question 2

What is the default method in the LOGISTIC procedure to handle observations with missing data?

Options:

A.

Missing values are imputed.

B.

Parameters are estimated accounting for the missing values.

C.

Parameter estimates are made on all available data.

D.

Only cases with variables that are fully populated are used.

Question 3

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.