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

1. Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
How many leaves are there in the decision tree?
Response:

A) 16-20
B) 21 or more
C) 1-10
D) 11-15

2. 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) 14.6216
B) 15
C) 66.6667
D) 80.3571

3. Which method of input selection for regression analysis evaluates the statistical significance of the total model to see if it improves on the baseline as the variables are added and once no further improvement is made then variable selection ends?
Select one:
Response:

A) Forward
B) Stepwise
C) Simple
D) Backward

4. Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
In the validation data, the lift corresponding to the fourth decile is in which of the following ranges?
Response:

A) 0-1.24999
B) 1.75 or more
C) 1.5-1.74999
D) 1.25-.49999

5. Refer to the exhibit:

The SAS data set retail contains information on the count of retail store sales based on the following item types: bargain, essential, gourmet, and health. Based on the results from the Cluster Profile node, which statement is true?
Select one:
Response:

A) The overall distribution of essential item sales is approximately normal and Segment 1 contains stores selling fewer than average essential items.
B) The overall distribution of bargain item sales is approximately normal and Segment 1 contains stores selling fewer than average bargain items.
C) The overall distribution of bargain item sales is left-skewed and Segment 4 contains stores selling fewer than average bargain items.
D) The overall distribution of essential item sales is right skewed and Segment 4 contains stores selling higher than average essential items.

Solutions: