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SAS Institute A00-240 Exam With Confidence Using Practice Dumps

Exam Code:
A00-240
Exam Name:
SAS Statistical Business Analysis SAS9: Regression and Model
Certification:
Statistical Business Analyst
Vendor:
SAS Institute
Questions:
99
Last Updated:
Jan 24, 2025
Exam Status:
Stable
SAS Institute A00-240

A00-240: Statistical Business Analyst Exam 2024 Study Guide Pdf and Test Engine

Are you worried about passing the SAS Institute A00-240 (SAS Statistical Business Analysis SAS9: Regression and Model) exam? Download the most recent SAS Institute A00-240 braindumps with answers that are 100% real. After downloading the SAS Institute A00-240 exam dumps training , you can receive 99 days of free updates, making this website one of the best options to save additional money. In order to help you prepare for the SAS Institute A00-240 exam questions and verified answers by IT certified experts, CertsTopics has put together a complete collection of dumps questions and answers. To help you prepare and pass the SAS Institute A00-240 exam on your first attempt, we have compiled actual exam questions and their answers. 

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

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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

The SAS data set RESULT contains the following variables:

  • Region (GrpA or GrpB)
  • Sales (dollars per year)

Which SAS programs can be used to find the p-value for comparing GrpA sales with GrpB sales? (Choose two.)

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 3

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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