Pass the SAS Institute Statistical Business Analyst A00-240 Questions and answers with CertsForce

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Questions # 21:

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

Question # 21

Options:

A.

Option A


B.

Option B


C.

Option C


D.

Option D


Expert Solution
Questions # 22:

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 VALID. 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 # 22

Options:

A.

Option A


B.

Option B


C.

Option C


D.

Option D


Expert Solution
Questions # 23:

Refer to the exhibit:

Question # 23

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


Expert Solution
Questions # 24:

This question will ask you to provide a missing option.

Given the following SAS program:

Question # 24

What option must be added to the program to obtain a data set containing Spearman statistics?

Options:

A.

OUTCORR=estimates


B.

OUTS=estimates


C.

OUT=estimates


D.

OUTPUT=estimates


Expert Solution
Questions # 25:

Refer to the exhibit.

Question # 25

Output from a multiple linear regression analysis is shown.

What is the most appropriate statement concerning collinearity between the input variables?

Options:

A.

Collinearity is a problem since all variance inflation values are less than 10.


B.

Collinearity is not a problem since all variance inflation values are less than 10.


C.

Collinearity is not a problem since all Pr>|t| values are less than 0.05.


D.

Collinearity is a problem since all Pr>|t| values are less than 0.05.


Expert Solution
Questions # 26:

Refer to the exhibit:

Question # 26

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.


Expert Solution
Questions # 27:

An analyst investigates Region (A, B, or C) as an input variable in a logistic regression model.

The analyst discovers that the probability of purchasing a certain item when Region = A is 1.

What problem does this illustrate?

Options:

A.

Collinearity


B.

Influential observations


C.

Quasi-complete separation


D.

Problems that arise due to missing values


Expert Solution
Questions # 28:

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?

Question # 28

Options:

A.

Solve


B.

Estimate


C.

Solution


D.

Est


Expert Solution
Questions # 29:

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.


Expert Solution
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