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

1. You are building a model for a marketing campaign. Every responder to the campaign solicitation will generate $471 in gross revenue. The average cost per solicitation is $66. Incorporating the above information in a decision matrix, what would be the decision threshold (probability cutoff) generated in your model?
You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A) 0.20
B) 0.14
C) 0.16
D) 0.86

2. Open the diagram labeled Practice A within the project labeled Practice A. Perform the following in SAS Enterprise Miner:

1. Set the Clustering method to Average.
2. Run the Cluster node.
What is the Cubic Clustering Criterion statistic for this clustering?
Response:

A) 67409.93
B) 5862.76
C) 14.69
D) 5.00

3. Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:

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

4. Which of the following is not true about results produced by the Regression node?
Response:

A) Fit Statistics can provide information that affects decision predictions, but does not affect estimate predictions.
B) Model Information provides you with information that includes the number of target categories and the number of model parameters.
C) Variable Summary information identifies the roles of variables used by the Regression node.
D) Type 3 Analysis of Effects provides you with information about the number of parameters that each input contributes to the model.

5. 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) 1.5-1.74999
B) 0-1.24999
C) 1.25-.49999
D) 1.75 or more

Solutions: