A00-240 Free Questions – SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential

1. Refer to the ROC curve:

As you move along the curve, what changes?

2. 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?

3. An analyst generates a model using the LOGISTIC procedure. They are now interested in getting the sensitivity and specificity statistics on a validation data set for a variety of cutoff values.

Which statement and option combination will generate these statistics?

4. In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)

5. Refer to the lift chart:

At a depth of 0.1, Lift = 3.14.

What does this mean?

6. Refer to the lift chart:

What does the reference line at lift = 1 corresponds to?

7. Suppose training data are oversampled in the event group to make the number of events and nonevents roughly equal. A logistic regression is run and the probabilities are output to a data set NEW and given the variable name PE. A decision rule considered is, “Classify data as an event if probability is greater than 0.5.” Also the data set NEW contains a variable TG that indicates whether there is an event (1=Event, 0= No event).

The following SAS program was used.

What does this program calculate?

8. In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?

9. Refer to the exhibit:

Based upon the comparative ROC plot for two competing models, which is the champion model and why?

10. A confusion matrix is created for data that were oversampled due to a rare target.

What values are not affected by this oversampling?