Exam Code: SZ0-240
Exam Name: SAS Statistical Business Analysis Using SAS 9: Regression and Modeling
Refer to the ROC curve:
A. The priors in the population
B. The true negative rate in the population
C. The proportion of events in the training data
D. The probability cutoff for scoring
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?
A. The sample means from the validation data set are applied to the training and test data sets.
B. The sample means from the training data set are applied to the validation and test data sets.
C. The sample means from the test data set are applied to the training and validation data sets.
D. The sample means from each partition of the data are applied to their own partition.
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?
A. Score data=valid1 out=roc;
B. Score data=valid1 outroc=roc;
C. mode1 resp(event= ‘1’) = gender region/outroc=roc;
D. mode1 resp(event"1") = gender region/ out=roc;
Which SAS program will divide the original data set into 60% training and 40% validation data sets, stratified by county?
A. Option A
B. Option B
C. Option C
D. Option D
In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)
A. Simple random sampling without replacement
B. Simple random sampling with replacement
C. Stratified random sampling without replacement
D. Sequential random sampling with replacement
Refer to the lift chart:
A. Selecting the top 10% of the population scored by the model should result in 3.14 times more
events than a random draw of 10%.
B. Selecting the observations with a response probability of at least 10% should result in 3.14 times
more events than a random draw of 10%.
C. Selecting the top 10% of the population scored by the model should result in 3.14 times greater
accuracy than a random draw of 10%.
D. Selecting the observations with a response probability of at least 10% should result in 3.14 times
greater accuracy than a random draw of 10%.
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