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SASInstitute A00-255 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Predictive Model Assessment and Implementation25–30%- Evaluate performance via profit/loss and comparison
- Adjust for oversampling and sampling methods
- Score and deploy models
- Apply appropriate fit statistics
Topic 2: Building Predictive Models35–40%- Build models using regression techniques
- Build models using neural networks
- Understand predictive modeling concepts
- Build models using decision trees
Topic 3: Data Sources20–25%- Create data sources from SAS tables
- Explore and assess data sources
- Modify and prepare source data for modeling
Topic 4: Pattern Analysis10–15%- Identify clusters and segments
- Interpret pattern discovery results

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

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) 0.14
C) 0.86
D) 0.16


2. Perform these tasks in SAS Enterprise Miner:
* Add a Decision Tree node, as shown below. (Make sure you use only default options in the Decision Tree node.)

* Run the Decision Tree node.
What is the probability that TARGET=0 for ID=000355 in the training data?
Response:

A) 0.9341825902
B) 0.0658174098
C) 0.9220647773
D) 0.077935227


3. Which method of input selection for regression analysis evaluates the statistical significance of the total model to see if it improves on the baseline as the variables are added and once no further improvement is made then variable selection ends?
Select one:
Response:

A) Backward
B) Stepwise
C) Simple
D) Forward


4. 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) Average Squared Error
B) Mean Square Error
C) Total Profit
D) 1 - Misclassification Rate


5. Perform these tasks in SAS Enterprise Miner:
- Add a Decision Tree node after the Impute node with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the decision tree to use 1 for Number of Surrogate Rules and Largest for Method in Subtree. Do not change any other property of the Decision Tree node.
- Add another Neural Network node after the decision tree with TARGET as the dependent variable and all other input variables as independent variables (main effects only). Configure the Neural Network model to use Average Error for Model Selection Criterion. Do not change any other property for the Neural Network node. Run the process flow.
Which of the following variables was used in the decision tree model?
Response:

A) IMP_TLSatCnt
B) TLDel3060Cnt24
C) InqFinanceCnt24.
D) TLDel90Cnt24


Solutions:

Question # 1
Answer: B
Question # 2
Answer: C
Question # 3
Answer: D
Question # 4
Answer: D
Question # 5
Answer: B

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