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SAS Statistical Business Analysis SAS9: Regression and Model

Last Update 21 hours ago Total Questions : 99

The SAS Statistical Business Analysis SAS9: Regression and Model content is now fully updated, with all current exam questions added 21 hours ago. Deciding to include A00-240 practice exam questions in your study plan goes far beyond basic test preparation.

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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

Question # 5

Refer to the REG procedure output:

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

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

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

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.

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

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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