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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.
Which of the following variable(s) is (are) statistically significant at the 5% level in the selected model?
Response:

A) TLTimeFirst
B) IMP_TLOpen24Pct
C) all of the above
D) TLDel3060Cnt24

2. A useful concept in logistic regression is the doubling amount. How would you calculate doubling amount for an input variable that has a parameter estimate of b1?
Response:

A) 2/log(b1)
B) 2*log(b1)
C) 0.69/b1
D) 2*b1

3. Assume you have two equally appealing logistic regression models. Then, if you have to select only one out of these two models, you should select the one that has which of the following?
Response:

A) smaller value of SBC (Schwarz,s Bayesian criterion)
B) smaller value of gamma
C) higher value of AIC (Akaike,s information criterion)
D) all of the above

4. Assume a variable is coded as follows: 1=unmarried, 2=married, 3=divorced, and 4=widowed. Then which of the following measurement levels should be selected in SAS Enterprise Miner for this variable?
Response:

A) Nominal
B) Interval
C) Unary
D) Ordinal

5. Assume the Target has an event proportion of 2% in the original data. Which of the following property values should be used in the Sample node of SAS Enterprise Miner to create a sample from that data with a balanced 50/50 split for Target?
Select one:
Response:

A) Sample Method: Stratify and Criterion: Equal
B) Sample Method: Random and Criterion: Proportional
C) Sample Method: Stratify and Criterion: Proportional
D) Sample Method: Random and Criterion: Equal

Solutions: