SASInstitute A00-240 問題集

質問 1：
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 not a problem since all variance inflation values are less than 10.
B. Collinearity is a problem since all variance inflation values are less than 10.
C. Collinearity is a problem since all Pr>|t| values are less than 0.05.
D. Collinearity is not a problem since all Pr>|t| values are less than 0.05.
正解：D

質問 2：
While building a predictive model, median imputations are performed while preparing the training data.
How should the imputations be addressed in the validation data?
A. The imputed values must be applied directly to the validation data without recalculation.
B. The imputed values must be recalculated using both the training and the validation data.
C. The imputed values are irrelevant to the validation data, and are not used.
D. The imputed values must be recalculated using the validation data.
正解：D

質問 3：
Within PROC GLM, the interaction between the two categorical predictors, Income and Gender, was shown to be significant. An item store was saved from the GLM analysis.
Which statement from PROC PLM would test the significance of Gender within each level of Income and adjust for multiple tests?
A. sliceby Income / adjust=tukey;
B. sliceby Gender / adjust=tukey;
C. slice Income*Gender / sliceby=Gender adjust=tukey;
D. slice Income*Gender / sliceby=Income adjust=tukey;
正解：A

質問 4：
Refer to the following exhibit:

What is a correct interpretation of this graph?
A. The association between the continuous predictor and the log-odds is quadratic.
B. The association between the continuous predictor and the binary response is quadratic.
C. The association between the binary predictor and the log-odds is quadratic.
D. The association between the continuous predictor and the continuous response is quadratic.
正解：A

質問 5：
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 6：
A predictive model uses a data set that has several variables with missing values.
What two problems can arise with this model? (Choose two.)
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.
正解：C,D

質問 7：
One common approach for predicting rare events in the LOGISTIC procedure is to build a model that disproportionately over-re presents those cases with an event occurring (e.g. a 50-50 event/non-event split).
What problem does this present?
A. Only the intercept estimate is biased.
B. Sensitivity estimates are biased.
C. Only the non-intercept parameter estimates are biased.
D. All parameter estimates are biased.
正解：A

質問 8：
Refer to the exhibit:

Which SAS program produced the graph?

A. Option A
B. Option C
C. Option D
D. Option B
正解：D

質問 9：
Given the following output from the LOGISTIC procedure:

Which variables, among those that are statistically significant at an alpha of 0.05, have the greatest and least relative importance on the fitted model?
A. Greatest: DOWN_AMTLeast: HOME
B. Greatest: MBALeast: CASH
C. Greatest: MBALeast: DOWN_AMT
D. Greatest: DOWN_AMTLeast: CASH
正解：D