SAS Institute A00-240 Online Practice Questions and Exam Preparation

SAS Institute A00-240 Online Questions & Answers

• Question 11:

  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
  A. 0.4115

• Question 12:

  Refer to the confusion matrix:

  

  Calculate the accuracy and error rate (0 - negative outcome, 1 - positive outcome)

  A. Accuracy = 58/102, Error Rate = 23/48
  B. Accuracy = 83/102, Error Rate = 67/102
  C. Accuracy = 25/150, Error Rate = 44/150
  D. Accuracy = 83/150, Error Rate = 67/150
  A. Accuracy = 58/102, Error Rate = 23/48

• Question 13:

  The standard form of a linear regression model is:

  

  Which statement best summarizes the assumptions placed on the errors?

  A. The errors are correlated, normally distributed with constant mean and zero variance.
  B. The errors are correlated, normally distributed with zero mean and constant variance.
  C. The errors are independent, normally distributed with constant mean and zero variance.
  D. The errors are independent, normally distributed with zero mean and constant variance.
  D. The errors are independent, normally distributed with zero mean and constant variance.

• Question 14:

  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.
  A. The SCORE statement in the LOGISTIC procedure returns only predicted probabilities, whereas the SCORE procedure returns only predicted logits.

• Question 15:

  Refer to the exhibit.

  

  Output from a multiple linear regression analysis is shown.

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

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

• Question 16:

  A confusion matrix is created for data that were oversampled due to a rare target. What values are not affected by this oversampling?

  A. Sensitivity and PV+
  B. Specificity and PV
  C. PV+ and PV
  D. Sensitivity and Specificity
  D. Sensitivity and Specificity

• Question 17:

  Which of the following describes a concordant pair of observations in the LOGISTIC procedure?

  A. An observation with the event has an equal probability as another observation with the event.
  B. An observation with the event has a lower predicted probability than the observation without the event.
  C. An observation with the event has an equal predicted probability as the observation without the event.
  D. An observation with the event has a higher predicted probability than the observation without the event
  D. An observation with the event has a higher predicted probability than the observation without the event

• Question 18:

  When mean imputation is performed on data after the data is partitioned for honest assessment, what is the most appropriate method for handling the mean imputation?

  A. The sample means from the validation data set are applied to the training and test data sets.
  B. The sample means from the training data set are applied to the validation and test data sets.
  C. The sample means from the test data set are applied to the training and validation data sets.
  D. The sample means from each partition of the data are applied to their own partition.
  B. The sample means from the training data set are applied to the validation and test data sets.

• Question 19:

  Refer to the exhibit:

  

  SAS output from the RSQUARE selection method, within the REG procedure, is shown. The top two models in each subset are given. Based on the AIC statistic, which model is the champion model?

  A. Age Weight RunTime RunPulse MaxPulse
  B. Age Weight RunTime RunPulse RestPulse MaxPulse
  C. RestPulse
  D. RunTime
  A. Age Weight RunTime RunPulse MaxPulse

• Question 20:

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

  

  A. Option A
  B. Option B
  C. Option C
  D. Option D
  B. Option B