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

1. What is the variable worth of the PromCntCardAll variable in Segment 1?
Select one:
Response:

A) 0.27649
B) 0.24169
C) 0.10844
D) 0.24914

2. An analyst is performing a market basket analysis (affinity analysis) on the purchase of Shaving Cream and Seltzer Water. The purchase data from a set of 250 customers is shown below:

What is the confidence of the rule "Shaving Cream implies Seltzer Water"? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A) 57%
B) 60%
C) 67%
D) 40%

3. 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.
For the validation data, in what range does cumulative percent captured response at the 60th percentile lie?
Response:

A) 75 or more
B) 0-24.99
C) 25-49.99
D) 50-74.99

4. 1. Create a project named Insurance, with a diagram named Explore.
2. Create the data source, DEVELOP, in SAS Enterprise Miner. DEVELOP is in the directory c:\workshop\Practice.
3. Set the role of all variables to Input, with the exception of the Target variable, Ins (1= has insurance, 0= does not have insurance).
4. Set the measurement level for the Target variable, Ins, to Binary.
5. Ensure that Branch and Res are the only variables with the measurement level of Nominal.
6. All other variables should be set to Interval or Binary.
7. Make sure that the default sampling method is random and that the seed is 12345.
The variable Branch has how many levels?
Response:

A) 12
B) 8
C) 47
D) 19

5. You are building a model to identify fraud. Your model will produce predictions that can be interpreted as the probability of fraud. You will pass on the top 100 scoring cases to management for investigation. Assume that you have sufficient data to hold out a validation and test data set for model evaluation.
Which selection would represent a reasonable ordering of fit statistics (best to worst) for this situation?
Select one:
Response:

A) R-square, AIC, K-S statistic
B) ASE, Lift for the top 10%, ROC index
C) Misclassification rate, ROC index, ASE
D) ROC index, ASE, misclassification rate

Solutions: