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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Building Predictive Models | 35–40% | - Build models using decision trees - Understand predictive modeling concepts - Build models using neural networks - Build models using regression techniques |
| Pattern Analysis | 10–15% | - Interpret pattern discovery results - Identify clusters and segments |
| Predictive Model Assessment and Implementation | 25–30% | - Adjust for oversampling and sampling methods - Score and deploy models - Evaluate performance via profit/loss and comparison - Apply appropriate fit statistics |
| Data Sources | 20–25% | - Create data sources from SAS tables - Explore and assess data sources - Modify and prepare source data for modeling |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Question #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. 0.86
C. 0.16
D. 0.14
Question #2
The number of hidden layers in this Neural Network model is which of the following?
Response:
A. 3
B. 1
C. 2
D. 4 or more
Question #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. 50-74.99
C. 0-24.99
D. 25-49.99
Question #4
If we were to add a Transformation node, what would be the default transformation for interval inputs for the present scenario?
Response:
A. Maximum Correlation
B. Maximum Normal
C. none of the above
D. Optimal
Question #5
Consider a binary target variable. Assume Accuracy is the desired assessment measure. Accuracy is not an option in the Decision Tree node. Which assessment measure can you use as a proxy for accuracy?
Select one:
Response:
A. Total Profit
B. 1 - Misclassification Rate
C. Average Squared Error
D. Mean Square Error
Solutions:
| Question #1 Correct Answer: D | Question #2 Correct Answer: B | Question #3 Correct Answer: A | Question #4 Correct Answer: C | Question #5 Correct Answer: B |


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