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SASInstitute A00-255 Exam : SAS Predictive Modeling Using SAS Enterprise Miner 14

A00-255 actual test
  • Exam Code: A00-255
  • Exam Name: SAS Predictive Modeling Using SAS Enterprise Miner 14
  • Updated: Sep 17, 2026
  • Q & A: 87 Questions and Answers
  • PDF Demo
  • PC Test Engine
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  • Total Price: $59.99  

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SASInstitute A00-255 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Pattern Analysis10-15%- Segmentation and Association Analysis
  • 1. Identify clusters using Cluster and Segment Profile nodes
  • 2. Perform sequence analysis and market basket analysis
  • 3. Perform association analysis
Topic 2: Building Predictive Models35-40%- Model Development
  • 1. Build decision tree models
  • 2. Build neural network models
  • 3. Describe predictive modeling concepts and terminology
  • 4. Build regression models
Topic 3: Data Sources20-25%- Prepare Source Data
  • 1. Modify source data
  • 2. Prepare data for predictive modeling
- Create and Explore Data Sources
  • 1. Create data sources from SAS tables in Enterprise Miner
  • 2. Explore and assess data sources
Topic 4: Predictive Model Assessment and Implementation25-30%- Model Evaluation
  • 1. Select appropriate fit statistics
  • 2. Compare models using Model Comparison node
  • 3. Use decision processing for oversampling adjustment
  • 4. Assess model performance using profit and loss information
- Model Deployment
  • 1. Score data sets within Enterprise Miner

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

Question #1

The Chi Square statistic for measuring association between the variables BanruptcyInd and TARGET is which of the following?
Response:

  • A. between 2.00 and 2.99
  • B. between 1.00 and 1.99
  • C. 3.00 or higher
  • D. less than 1.00
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #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.
In the decision tree model, what is the importance of the variable InqCnt06?
Response:

  • A. 0.30-0.449999
  • B. 0.45 or higher
  • C. 0.15-0.299999
  • D. less than 0.149999
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #3

Which method of input selection for regression analysis evaluates the statistical significance of all included inputs after each input is added?
Select one:
Response:

  • A. Backward
  • B. Stepwise
  • C. Simple
  • D. Forward
Reveal Solution  Discussion  0

Correct Answer: B  🗳️

Question #4

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. $9,586.55
  • B. $0.00
  • C. $8,711.65
  • D. $11,142.45
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #5

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.
In the training data set, consider only those observations for which the actual value of the target variable equals 1, TARGET=1. What percentage of these observations is being correctly predicted by the decision tree?
Response:

  • A. 15
  • B. 14.6216
  • C. 80.3571
  • D. 66.6667
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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