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Question # 4

A researcher has several variables that could be possible predictors for the final model. There is interest in checking all 2-way interactions for possible entry to the model. The researcher has decided to use forward selection within PROC LOGISTIC. Fill in the missing code option that will ensure that all 2-way interactions will be considered for entry.

A.

start = 5

B.

include = 4

C.

include = 5

D.

start = 4

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Question # 5

Refer to the REG procedure output:

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

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Question # 6

Refer to the confusion matrix:

Calculate the sensitivity. (0 - negative outcome, 1 - positive outcome)

Click the calculator button to display a calculator if needed.

A.

25/48

B.

58/102

C.

25/B9

D.

58/81

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Question # 7

Refer to the REG procedure output:

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

A.

0.4115

B.

0.6994

C.

0.5884

D.

0.1372

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Question # 8

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.)

A.

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

B.

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

C.

Use subject matter expertise to combine stores that are similar.

D.

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

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Question # 9

Refer to the exhibit:

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

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

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Question # 10

Suppose training data are oversampled in the event group to make the number of events and non-events roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the variable name PE. A decision rule considered is, "Classify data as an event if probability is greater than 0.5." Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0= No event).

The following SAS program was used.

What does this program calculate?

A.

Depth

B.

Sensitivity

C.

Specificity

D.

Positive predictive value

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Question # 11

This question will ask you to provide missing code segments.

A logistic regression model was fit on a data set where 40% of the outcomes were events (TARGET=1) and 60% were non-events (TARGET=0). The analyst knows that the population where the model will be deployed has 5% events and 95% non-events. The analyst also knows that the company's profit margin for correctly targeted events is nine times higher than the company's loss for incorrectly targeted non-event.

Given the following SAS program:

What X and Y values should be added to the program to correctly score the data?

A.

X=40, Y=10

B.

X=.05, Y=10

C.

X=.05, Y=.40

D.

X=.10, Y=05

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Question # 12

Which SAS program will best identify influential observations in a multiple regression application?

A.

Option A

B.

Option B

C.

Option C

D.

Option D

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Question # 13

The question will ask you to provide a missing statement. Given the following SAS program:

Which SAS statement will complete the program to correctly score the data set NEW_DATA?

A.

Score data data=MYDIR.NEW_DATA out=scores;

B.

Score data data=MYDIR.NEW_DATA output=scores;

C.

Score data=HYDIR.NEU_DATA output=scores;

D.

Score data=MYDIR, NEW DATA out=scores;

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Question # 14

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?

A.

Solve

B.

Estimate

C.

Solution

D.

Est

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