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SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:

1. Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
Consider the variable TLCnt03 in the selected model. Based on the model results, changing this variable by 1 unit will result in which of the following?
Response:

A) change of odds for TARGET=1 by a factor 0.3457
B) reduction of odds for TARGET=1 by 0.3457
C) change of odds for TARGET=1 by a factor 0.708
D) reduction of odds for TARGET=1 by 0.708

2. What is the kurtosis value for the variable TLDel60Cnt24?
Response:

A) between 10 and 13.99
B) less than 10
C) between 14 and 16.99
D) 17 or higher

3. Transformation of input variables to make their distributions more symmetric will likely have what impact in a logistic regression?
Select one:
Response:

A) neither increase nor decrease the performance of logistic regression
B) decrease the performance of logistic regression
C) create convergence problems in maximum likelihood estimation
D) increase the performance of logistic regression

4. Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

* Run the Decision Tree node.
In the training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:

A) 80.3571
B) 15
C) 66.6667
D) 14.6216

5. A separate sample has been taken such that the target distribution in the separate sample is different from the target distribution in the original sample.
What should be adjusted?
Select one:
Response:

A) lift
B) sensitivity
C) specificity
D) confidence intervals

Solutions: