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

1. 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) 14.69
B) 5862.76
C) 5.00
D) 67409.93

2. Which of the following solves problems for you when you impute missing values?
Response:

A) When you impute a synthetic value, it replaces missing values with 1 or 0.
B) When you impute a synthetic value, predictive information is retained.
C) When you impute a synthetic value, it eliminates the incomplete case problem.
D) When you impute a synthetic value, each missing value becomes an input to the model.

3. Refer to the following profit matrix and confusion matrix for a campaign soliciting product purchases. The predicted variable is a binary outcome.

Based on the above tables, what is the average profit? You may use a calculator for this question. On the certification exam, an on-screen calculator is provided for you.
Select one:
Response:

A) 69
B) 6.9
C) 690
D) 86.25

4. 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) 0.69/b1
C) 2*b1
D) 2/log(b1)

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: