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SAS Statistical Business Analysis SAS9: Regression and Model

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Question # 1

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.

Discussion 0
Question # 2

Refer to the exhibit:

Question # 2

Which statement is true, based on the plots above?

Options:

A.  

Approximately twice as many customers with the top ten percent of predicted probabilities are expected to have a positive versus negative event.

B.  

Approximately ten percent of a randomly selected subset of twenty percent of the customers are expected to have a positive event.

C.  

Approximately twenty percent of the customers with a predicted score of 3 have a positive predicted class.

D.  

Approximately ten percent of those customers with the top twenty percent of predicted probabilities are expected to have a positive event.

Discussion 0
Question # 3

Assume a $10 cost for soliciting a non-responder and a $200 profit for soliciting a responder. The logistic regression model gives a probability score named P_R on a SAS data set called VALI

D.  

The VALID data set contains the responder variable Pinch, a 1/0 variable coded as 1 for responder. Customers will be solicited when their probability score is more than 0.05.

Which SAS program computes the profit for each customer in the data set VALID?

Question # 3

Options:

A.  

Option A

B.  

Option B

C.  

Option C

D.  

Option D

Discussion 0
Question # 4

Refer to the REG procedure output:

Question # 4

Click on the calculator button to display a calculator if needed.

Options:

A.  

0.4115

B.  

0.6994

C.  

0.5884

D.  

0.1372

Discussion 0
Question # 5

The PROC LOGISTIC options SELECTION=SCORE and BEST=2 are used in a MODEL statement to generate a series of predictive models. The models are assigned numbers in order from 1 to 99 reflecting the fact that there are 50 candidate input variables. Results from the collection of derived models are used to generate the following plot of overall average profit by model number. Results are restricted to models with at least 9 inputs and at most 40 inputs.

Question # 5

The maximum value for the training data occurs for model number 46, and the maximum value for the validation data occurs for model number 43.

If you base model selection solely on overall average profit, what is the correct choice?

Options:

A.  

Select model 46

B.  

Select model 43

C.  

Select model 45

D.  

Select model 21

Discussion 0
Question # 6

Refer to the exhibit:

Question # 6

Based upon the comparative ROC plot for two competing models, which is the champion model and why?

Options:

A.  

Candidate 1, because the area outside the curve is greater

B.  

Candidate 2, because the area under the curve is greater

C.  

Candidate 1, because it is closer to the diagonal reference curve

D.  

Candidate 2, because it shows less over fit than Candidate 1

Discussion 0
Question # 7

Refer to the exhibit:

Question # 7

On the Gains Chart, what is the correct interpretation of the horizontal reference line?

Options:

A.  

the proportion of cases that cannot be classified

B.  

the probability of a false negative

C.  

the probability of a false positive

D.  

the prior event rate

Discussion 0
Question # 8

There are missing values in the input variables for a regression application.

Which SAS procedure provides a viable solution?

Options:

A.  

GLM

B.  

VARCLUS

C.  

STDI2E

D.  

CLUSTER

Discussion 0
Question # 9

This question will ask you to provide a segment of missing code.

The following code is used to create missing value indicator variables for input variables, fred1 to fred7.

Question # 9

Which segment of code would complete the task?

Question # 9

Options:

A.  

Option A

B.  

Option B

C.  

Option C

D.  

Option D

Discussion 0
Question # 10

Spearman statistics in the CORR procedure are useful for screening for irrelevant variables by investigating the association between which function of the input variables?

Options:

A.  

Concordant and discordant pairs of ranked observations

B.  

Logit link (log (p/1-p))

C.  

Rank-ordered values of the variables

D.  

Weighted sum of chi-square statistics for 2x2 tables

Discussion 0
Question # 11

Identify the correct SAS program for fitting a multiple linear regression model with dependent variable (y) and four predictor variables (x1-x4).

Question # 11

Options:

A.  

Option A

B.  

Option B

C.  

Option C

D.  

Option D

Discussion 0
Question # 12

Refer to the REG procedure output:

Question # 12

Calculate the coefficient of determination, R-Square.

Enter your numeric answer in the space below. Round to 4 decimal places (example: n.nnnn).

Options:

Discussion 0
Question # 13

Refer to the exhibit.

Question # 13

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.

Discussion 0
Question # 14

Refer to the REG procedure output:

Question # 14

How many observations are used in the analysis? Enter your numeric answer in the space below.

Options:

Discussion 0
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