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SASInstitute A00-255 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Building Predictive Models | 35–40% | - Build models using regression techniques - Understand predictive modeling concepts - Build models using neural networks - Build models using decision trees |
| Pattern Analysis | 10–15% | - Identify clusters and segments - Interpret pattern discovery results |
| Predictive Model Assessment and Implementation | 25–30% | - Apply appropriate fit statistics - Adjust for oversampling and sampling methods - Evaluate performance via profit/loss and comparison - Score and deploy models |
| Data Sources | 20–25% | - Create data sources from SAS tables - Modify and prepare source data for modeling - Explore and assess data sources |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
What is the purpose of the Kass (Bonferroni) adjustment in the decision tree split-search algorithm?
Select one:
Response:
- A. To give categorical inputs a greater chance to be used the split.
- B. To reduce the number of surrogate splitting rules.
- C. To ensure that the choice of split is not influenced by input measurement scale.
- D. To ensure a non-negative logworth value.
Correct Answer: C 🗳️
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.
What is the mean credit card balance (CCBal) of the customers with a variable annuity?
Response:
- A. $0.00
- B. $11,142.45
- C. $8,711.65
- D. $9,586.55
Correct Answer: D 🗳️
Sometimes in predictive modeling we build models using a sample that has a primary outcome proportion different from true population proportion. This is usually done when the ratio of primary to secondary outcomes in a binary target variable in the population is close to which of the following?
Response:
- A. 1
- B. 1.2
- C. 0.05
- D. 0.8
Correct Answer: C 🗳️
How many unique indicator variables were created during imputation?
Response:
- A. 11-20
- B. none
- C. 1-10
- D. 21 or higher
Correct Answer: A 🗳️
A separate sample has been taken such that the target distribution in the separate sample is different from the target distribution in the original sample.
What should be adjusted?
Select one:
Response:
- A. lift
- B. confidence intervals
- C. sensitivity
- D. specificity
Correct Answer: A 🗳️
