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January 11, 2018

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Q1. 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

Answer: A


Q2. This question will ask you to provide a missing option. Given the following SAS program:

 

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

A. OUTPUT=estimates

B. OUTP=estimates

C. OUTSTAT=estimates

D. OUTCORR=estimates

Answer: B


Q3. What is a drawback to performing data cleansing (imputation, transformations, etc.) on raw data prior to partitioning the data for honest assessment as opposed to performing the data cleansing after partitioning the data?

A. It violates assumptions of the model.

B. It requires extra computational effort and time.

C. It omits the training (and test) data sets from the benefits of the cleansing methods.

D. There is no ability to compare the effectiveness of different cleansing methods.

Answer: D


Q4. Which SAS program will correctly use backward elimination selection criterion within the REG procedure?

 

A. Option A

B. Option B

C. Option C

D. Option D

Answer: B


Q5. Including redundant input variables in a regression model can:

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.

Answer: B


Q6. A financial services manager wants to assess the probability that certain clients will default on their Home Equity Line of Credit (HELOC). A former employee left the code listed below.

 

The training data set is named HELOC, while a similar data set of more recent clients is named RECENT_HELOC. Which SAS data steps will calculate the predicted probability of default on recent clients? (Choose two.)

 

A. Option A

B. Option B

C. Option C

D. Option D

Answer: A,B


Q7. Consider scoring new observations in the SCORE procedure versus the SCORE statement in the LOGISTIC procedure.

Which statement is true?

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.

Answer: A


Q8. Which statistic, calculated from a validation sample, can help decide which model to use for prediction of a binary target variable?

A. Adjusted R Square

B. Mallow's Cp

C. Chi Square

D. Average Squared Error

Answer: D


Q9. Including redundant input variables in a regression model can:

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.

Answer: B


Q10. Consider scoring new observations in the SCORE procedure versus the SCORE statement in the LOGISTIC procedure.

Which statement is true?

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.

Answer: A



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