SAS Certified Statistical Business Analysts practice test
SAS Statistical Business Analysts
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Question 1 of 7
1. Question1 points
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?
Question 2 of 7
2. Question1 points
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?
Question 3 of 7
3. Question1 points
In partitioning data for model assessment, which sampling methods are acceptable? (Choose two.)
Question 4 of 7
4. Question1 points
A confusion matrix is created for data that were oversampled due to a rare target.
What values are not affected by this oversampling?
Question 5 of 7
5. Question1 points
An analyst has a sufficient volume of data to perform a 3-way partition of the data into training, validation, and test sets to perform honest assessment during the model building process.
What is the purpose of the test data set?
Question 6 of 7
6. Question1 points
The total modeling data has been split into training, validation, and test data. What is the best data to use for model assessment?
Question 7 of 7
7. Question1 points
What is a drawback to performing data cleansing (imputation, transformations, etc.) on raw data prior to partitioning the data for honest assessment as opposed to performing the data cleansing
after partitioning the data?
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