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SASInstitute A00-255 Exam Syllabus Topics:

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

Question 1

What is the kurtosis value for the variable TLDel60Cnt24?
Response:

A. between 14 and 16.99
B. 17 or higher
C. between 10 and 13.99
D. less than 10

Question 2

1. Define a new data source, PatternData, in SAS Enterprise Miner (SAS data set Patterndata.sas7bdat in the zip file distributed with this practice exam).
2. Set the role of all variables to Input, with the exception set the ID variable role to ID.
3. Set the measurement level for all variables to Interval, except:
- Set DemHomeOwner and StatusCatStarAll to Binary.
- Set DemCluster, DemGender, ID, and StatusCat96NK to Nominal.
4. Create a new diagram (name it Section6) within the project labeled Test.
5. Add the data source, PatternData, to this diagram. Make sure the variable roles and measurements are the same as in the table below. (Check the highlighted rows carefully and reset roles/levels as needed.)
6. Connect a Cluster node to the data source.
7. Modify the Cluster node to exclude nominal and binary input variables.
8. Run the Cluster node.

How many clusters are created by the Cluster node?
Response:

A. 9
B. 8
C. 3
D. 6

Question 3

Which statement describes the Decision Tree Split Search mechanism for categorical inputs?
Select one:
Response:

A. The average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
B. The levels that have target rate of 0 or 100% are re-binned first, then weighted and the weights are used for testing.
C. A clustering mechanism eliminates observations in outlier clusters as potential split points as a first step. Then, for the remaining observations, the average target value is calculated for each level, and then passed on for testing if it is the optimal split point.
D. All levels are weighted and the weights are used for testing.

Question 4

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

Question 5

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

Solutions: