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SASInstitute A00-255 Exam Syllabus Topics:

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

1. Impute the missing values for the variable TLSum using the Tree method. What is the mean of the new variable (with the imputed values)?
Response:

A) 30,000-39,999.99
B) 40,000 or higher
C) 20,000-29,999.99
D) less than 19,999.99

2. For the variable TLCnt24, apply a Max Normal transformation. What transformation was selected by SAS Enterprise Miner?
Response:

A) Square Root
B) Square
C) Exponential
D) Log

3. Refer to the exhibit:

The SAS data set retail contains information on the count of retail store sales based on the following item types: bargain, essential, gourmet, and health. Based on the results from the Cluster Profile node, which statement is true?
Select one:
Response:

A) The overall distribution of bargain item sales is approximately normal and Segment 1 contains stores selling fewer than average bargain items.
B) The overall distribution of essential item sales is right skewed and Segment 4 contains stores selling higher than average essential items.
C) The overall distribution of essential item sales is approximately normal and Segment 1 contains stores selling fewer than average essential items.
D) The overall distribution of bargain item sales is left-skewed and Segment 4 contains stores selling fewer than average bargain items.

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

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.
How many leaves are there in the decision tree?
Response:

A) 16-20
B) 11-15
C) 21 or more
D) 1-10

Solutions: