Black Friday Special Limited Time 70% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: 70special

Examstrust Logo
examstrust mcafee
  1. Home
  2. SAS Institute
  3. Statistical Business Analyst
  4. A00-240 - SAS Statistical Business Analysis SAS9: Regression and Model

SAS Institute A00-240 SAS Statistical Business Analysis SAS9: Regression and Model Exam Practice Test

Page: 1 / 10
Total 99 questions
Get A00-240 Full Access Download A00-240 PDF

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

Testing Engine

  • Product Type: Testing Engine
$37.5  $124.99
Add to Cart

PDF + Testing Engine

  • Product Type: PDF + Testing Engine
$52.5  $174.99
Add to Cart

PDF Study Guide

  • Product Type: PDF Study Guide
$33  $109.99
Add to Cart
Question 1

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?

Options:

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 2

What does the Pearson product moment correlation coefficient measure?

Options:

A.

nonlinear and nonmonotonic association between two variables

B.

linear and monotonic association between two variables

C.

linear and nonmonotonic association between two variables

D.

nonlinear and monotonic association between two variables

Question 3

Refer to the lift chart:

At a depth of 0.1, Lift = 3.14. What does this mean?

Options:

A.

Selecting the top 10% of the population scored by the model should result in 3.14 times more events than a random draw of 10%.

B.

Selecting the observations with a response probability of at least 10% should result in 3.14 times more events than a random draw of 10%.

C.

Selecting the top 10% of the population scored by the model should result in 3.14 times greater accuracy than a random draw of 10%.

D.

Selecting the observations with a response probability of at least 10% should result in 3.14 times greater accuracy than a random draw of 10%.

Question 4

Including redundant input variables in a regression model can:

Options:

A.

Stabilize parameter estimates and increase the risk of overfitting.

B.

Destabilize parameter estimates and increase the risk of overfitting.

C.

Stabilize parameter estimates and decrease the risk of overfitting.

D.

Destabilize parameter estimates and decrease the risk of overfitting.

Question 5

Refer to the ROC curve:

As you move along the curve, what changes?

Options:

A.

The priors in the population

B.

The true negative rate in the population

C.

The proportion of events in the training data

D.

The probability cutoff for scoring

Question 6

Refer to the exhibit.

Given alpha=0.02, which conclusion is justified regarding percentage of body fat, comparing small (S), medium (M), and large (L) wrist sizes?

Options:

A.

Medium wrist size is significantly different than small wrist size.

B.

Large wrist size is significantly different than medium wrist size.

C.

Large wrist size is significantly different than small wrist size.

D.

There is no significant difference due to wrist size.

Question 7

Which SAS program will correctly use backward elimination selection criterion within the REG procedure?

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 8

Consider scoring new observations in the SCORE procedure versus the SCORE statement in the LOGISTIC procedure.

Which statement is true?

Options:

A.

The SCORE statement in the LOGISTIC procedure returns only predicted probabilities, whereas the SCORE procedure returns only predicted logits.

B.

The SCORE statement in the LOGISTIC procedure returns only predicted logits, whereas the SCORE procedure returns only predicted probabilities.

C.

Unlike the SCORE procedure, the SCORE statement in the LOGISTIC procedure produces both predicted probabilities and predicted logits.

D.

The SCORE procedure and the SCORE statement in the LOGISTIC procedure produce the same output.

Question 9

Which SAS program will detect collinearity in a multiple regression application?

Options:

A.

Option A

B.

Option B

C.

Option C

D.

Option D

Question 10

Which statistic is based on the maximum vertical distance between the primary event EDF and the secondary event EDF?

Options:

A.

KS

B.

SBC

C.

Max EDF

D.

Brier Score

Question 11

This question will ask you to provide a missing option.

A business analyst is investigating the differences in sales figures across 8 sales regions. The analyst is interested in viewing the regression equation parameter estimates for each of the design variables.

Which option completes the program to produce the regression equation parameter estimates?

Options:

A.

Solve

B.

Estimate

C.

Solution

D.

Est

Question 12

The selection criterion used in the forward selection method in the REG procedure is:

Options:

A.

Adjusted R-Square

B.

SLE

C.

Mallows' Cp

D.

AIC

Question 13

In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

Options:

A.

Training: 50% Validation: 0% Testing: 50%

B.

Training: 100% Validation: 0% Testing: 0%

C.

Training: 0% Validation: 100% Testing: 0%

D.

Training: 50% Validation: 50% Testing: 0%

Question 14

An analyst generates a model using the LOGISTIC procedure. They are now interested in getting the sensitivity and specificity statistics on a validation data set for a variety of cutoff values.

Which statement and option combination will generate these statistics?

Options:

A.

Score data=valid1 out=roc;

B.

Score data=valid1 outroc=roc;

C.

mode1 resp(event= '1') = gender region/outroc=roc;

D.

mode1 resp(event"1") = gender region/ out=roc;

Load More A00-240 Questions
Page: 1 / 10
Total 99 questions
Get A00-240 Full Access Download A00-240 PDF