SAS Institute SAS Institute Certifications A00-240 Questions & Answers

• Question 61:

  Refer to the following exhibit:

  

  What is a correct interpretation of this graph?

  A. The association between the continuous predictor and the binary response is quadratic.

  B. The association between the continuous predictor and the log-odds is quadratic.

  C. The association between the continuous predictor and the continuous response is quadratic.

  D. The association between the binary predictor and the log-odds is quadratic.

  Correct Answer: B

• Question 62:

  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.

  Correct Answer: B

• Question 63:

  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.

  Correct Answer: BC

• Question 64:

  An analyst fits a logistic regression model to predict whether or not a client will default on a loan. One of the predictors in the model is agent, and each agent serves 15-20 clients each. The model fails to converge. The analyst prints the summarized data, showing the number of defaulted loans per agent. See the partial output below:

  

  What is the most likely reason that the model fails to converge?

  A. There is quasi-complete separation in the data.

  B. There is collinearity among the predictors.

  C. There are missing values in the data.

  D. There are too many observations in the data.

  Correct Answer: A

• Question 65:

  Screening for non-linearity in binary logistic regression can be achieved by visualizing:

  A. A scatter plot of binary response versus a predictor variable.

  B. A trend plot of empirical logit versus a predictor variable.

  C. A logistic regression plot of predicted probability values versus a predictor variable.

  D. A box plot of the odds ratio values versus a predictor variable.

  Correct Answer: B

• Question 66:

  Given the following SAS data set TEST:

  

  Which SAS program is NOT a correct way to create dummy variables?

  

  A. Option A

  B. Option B

  C. Option C

  D. Option D

  Correct Answer: D

• Question 67:

  There are missing values in the input variables for a regression application.

  Which SAS procedure provides a viable solution?

  A. GLM

  B. VARCLUS

  C. STDI2E

  D. CLUSTER

  Correct Answer: C

• Question 68:

  An analyst compares the mean salaries of men and women working at a company. The SAS data set SALARY contains variables:

  1.

  Gender (M or F)

  2.

  Pay (dollars per year)

  Which SAS programs can be used to find the p-value for comparing men's salaries with women's salaries? (Choose two.)

  

  A. Option A

  B. Option B

  C. Option C

  D. Option D

  Correct Answer: AB

• Question 69:

  Given the following GLM procedure output:

  

  Which statement is correct at an alpha level of 0.05?

  A. School*Gender should be removed because it is non-significant.

  B. Gender should be removed because it is non-significant.

  C. School should be removed because it is significant.

  D. Gender should not be removed due to its involvement in the significant interaction.

  Correct Answer: D

• Question 70:

  Refer to the exhibit:

  

  The box plot was used to analyze daily sales data following three different ad campaigns. The business analyst concludes that one of the assumptions of ANOVA was violated.

  Which assumption has been violated and why?

  A. Normality, because Prob > F < .0001.

  B. Normality, because the interquartile ranges are different in different ad campaigns.

  C. Constant variance, because Prob > F < .0001.

  D. Constant variance, because the interquartile ranges are different in different ad campaigns.

  Correct Answer: D