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SASInstitute A00-255 Exam Syllabus Topics:

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

1. 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 percentage of all observations is being correctly predicted in the test data set by the decision tree?
Response:

A) 16.8874%
B) 84.5212%
C) 85.2222%
D) 83.1126%

2. 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) 40,000 or higher
B) 20,000-29,999.99
C) 30,000-39,999.99
D) less than 19,999.99

3. For the Variable Selection node, which statement describes the R-squared variable selection criterion?
Select one:
Response:

A) It looks for a set of colinear inputs that correlate with the target.
B) It uses a chi-squared Decision Tree with no Bonferoni adjustment to select the relevant inputs.
C) It uses a squared correlation and then a stepwise regression to eliminate irrelevant inputs.
D) It is similar to a decision tree algorithm in being able to detect nonlinear and non-additive relationships between inputs and the target.

4. Which model was picked as the best model by SAS Enterprise Miner?
Response:

A) Regression
B) None of the above
C) Decision Tree
D) Decision Tree (3-way)

5. For the variable InqTimeLast, which term best describes the shape of its distribution?
Response:

A) symmetric
B) bimodal
C) right skewed
D) left skewed

Solutions: