File Info
| Exam | SAS Statistical Business Analysis SAS9: Regression and Model |
| Number | A00-240 |
| File Name | SASInstitute.A00-240.Pass4Sure.2020-02-04.59q.vcex |
| Size | 4 MB |
| Posted | Feb 04, 2020 |
| Download | SASInstitute.A00-240.Pass4Sure.2020-02-04.59q.vcex |
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Demo Questions
Question 1
Refer to the ROC curve:
As you move along the curve, what changes?
- The priors in the population
- The true negative rate in the population
- The proportion of events in the training data
- The probability cutoff for scoring
Correct answer: D
Question 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?
- The sample means from the validation data set are applied to the training and test data sets.
- The sample means from the training data set are applied to the validation and test data sets.
- The sample means from the test data set are applied to the training and validation data sets.
- The sample means from each partition of the data are applied to their own partition.
Correct answer: B
Question 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?
- Score data=valid1 out=roc;
- Score data=valid1 outroc=roc;
- mode1 resp(event= '1') = gender region/outroc=roc;
- mode1 resp(event"1") = gender region/ out=roc;
Correct answer: B
Question 4
In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)
- Simple random sampling without replacement
- Simple random sampling with replacement
- Stratified random sampling without replacement
- Sequential random sampling with replacement
Correct answer: AC
Question 5
Refer to the lift chart:
What does the reference line at lift = 1 corresponds to?
- The predicted lift for the best 50% of validation data cases
- The predicted lift if the entire population is scored as event cases
- The predicted lift if none of the population are scored as event cases
- The predicted lift if 50% of the population are randomly scored as event cases
Correct answer: B
Question 6
Suppose training data are oversampled in the event group to make the number of events and non-events 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?
- Depth
- Sensitivity
- Specificity
- Positive predictive value
Correct answer: B
Question 7
Refer to the exhibit:
The plots represent two models, A and B, being fit to the same two data sets, training and validation.
Model A is 90.5% accurate at distinguishing blue from red on the training data and 75.5% accurate at doing the same on validation data. Model B is 83% accurate at distinguishing blue from red on the training data and 78.3% accurate at doing the same on the validation data.
Which of the two models should be selected and why?
- Model A. It is more complex with a higher accuracy than model B on training data.
- Model A. It performs better on the boundary for the training data.
- Model B. It is more complex with a higher accuracy than model A on validation data.
- Model B. It is simpler with a higher accuracy than model A on validation data.
Correct answer: D
Question 8
Assume a $10 cost for soliciting a non-responder and a $200 profit for soliciting a responder. The logistic regression model gives a probability score named P_R on a SAS data set called VALID. The VALID data set contains the responder variable Pinch, a 1/0 variable coded as 1 for responder. Customers will be solicited when their probability score is more than 0.05.
Which SAS program computes the profit for each customer in the data set VALID?
- Option A
- Option B
- Option C
- Option D
Correct answer: A
Question 9
In order to perform honest assessment on a predictive model, what is an acceptable division between training, validation, and testing data?
- Training: 50% Validation: 0% Testing: 50%
- Training: 100% Validation: 0% Testing: 0%
- Training: 0% Validation: 100% Testing: 0%
- Training: 50% Validation: 50% Testing: 0%
Correct answer: D
Question 10
Refer to the exhibit:
Based upon the comparative ROC plot for two competing models, which is the champion model and why?
- Candidate 1, because the area outside the curve is greater
- Candidate 2, because the area under the curve is greater
- Candidate 1, because it is closer to the diagonal reference curve
- Candidate 2, because it shows less over fit than Candidate 1
Correct answer: B
