SASInstitute A00-240 問題集

質問 1：
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 C
C. Option D
D. Option B
正解：A,D

質問 2：
In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)
A. Stratified random sampling without replacement
B. Simple random sampling without replacement
C. Sequential random sampling with replacement
D. Simple random sampling with replacement
正解：A,B

質問 3：
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?
A. Problems that arise due to missing values
B. Quasi-complete separation
C. Collinearity
D. Influential observations
正解：B

質問 4：
Which characteristic of Studentized residuals indicate potential outliers?
A. Only studentized residuals less than two and greater than negative two
B. Only studentized residuals greater than negative two
C. Only studentized residuals greater than two
D. Only studentized residuals less than negative two and greater than two
正解：C

質問 5：
Which method is NOT an appropriate way to score new observations with a known target in a logistic regression model?
A. Use the saved parameter estimates from the LOGISTIC procedure and score new observations in the SCORE procedure.
B. Augment the training data set with new observations and set their responses to missing.
C. Augment the training data set with new observations and rerun the LOGISTIC procedure.
D. Use the SCORE statement in the LOGISTIC procedure.
正解：C

質問 6：
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. Chi Square
C. Average Squared Error
D. Mallow's Cp
正解：C

質問 7：
Customers were surveyed to assess their intent to purchase a product. An analyst divided the customers into groups defined by the company's pre-assigned market segments and tested for difference in the customers' average intent to purchase. The following is the output from the GLM procedure:

What percentage of customers' intent to purchase is explained by market segment?
Click the calculator button to display a calculator if needed.
A. <0.01%
B. 76%
C. 35%
D. 65%
正解：B

質問 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. Cluster by using Greenacre's method to combine stores that are similar.
B. Eliminate store_id as a predictor in the model because it has too many levels to be feasible.
C. Randomly combine the stores into five groups to keep the stochastic variation among the observations intact.
D. Use subject matter expertise to combine stores that are similar.
正解：A,D

質問 9：
Given the following LOGISTIC procedure:

What is the difference between the datasets OUTFILEJ and OUTFILE_2?
A. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored probabilities
B. OUTFILE_1 contains the model goodness of fit statistics while OUTFILE_2 contains the newly scored logits.
C. OUTFILEJ contains the final parameter estimates and Wald Chi-Square values while OUTFILE_2 contains the newly scored probabilities.
D. OUTFILE_1 contains the final parameter estimates while OUTFILE_2 contains the newly scored probabilities.
正解：D