Download SASInstitute : A00-255 Questions & Answers as PDF & Test Software
Updated: Aug 12, 2026
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SASInstitute A00-255 Exam Overview:
| Certification Vendor: | SAS Institute |
| Exam Name: | SAS Predictive Modeling Using SAS Enterprise Miner 14 |
| Exam Number: | A00-255 |
| Exam Duration: | 165 minutes |
| Certificate Validity Period: | No expiration |
| Available Languages: | English |
| Passing Score: | 725/1000 |
| Real Exam Qty: | 55-60 |
| Exam Price: | USD 250 |
| Related Certifications: | SAS Certified Predictive Modeler Using SAS Enterprise Miner 14 SAS Certified Advanced Analytics Professional SAS Certified Data Scientist |
| Exam Format: | Multiple-choice, Short-answer, Performance-based |
| Sample Questions: | SASInstitute A00-255 Sample Questions |
| Exam Way: | Computer-based exam delivered through Pearson VUE testing centers and online proctored testing. |
| Pre Condition: | No mandatory prerequisite. Candidates should have hands-on experience with SAS Enterprise Miner and predictive modeling concepts. |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/predictive-modeler.html |
SASInstitute A00-255 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Sources | 20-25% | - Prepare Source Data
|
| Topic 2: Building Predictive Models | 35-40% | - Model Development
|
| Topic 3: Predictive Model Assessment and Implementation | 25-30% | - Model Evaluation
|
| Topic 4: Pattern Analysis | 10-15% | - Segmentation and Association Analysis
|
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
1. The number of neurons in this Neural Network model is which of the following:
Response:
A) 3
B) 4 or more
C) 1
D) 2
2. 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.
The number of parameters (weights) estimated by the Neural Network model is in which of the following ranges?
Response:
A) 11-15
B) 6-10
C) 16 or more
D) less than or equal to 5
3. 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) 0.45 or higher
B) less than 0.149999
C) 0.15-0.299999
D) 0.30-0.449999
4. 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) 0.077935227
C) 0.0658174098
D) 0.9220647773
5. You are building a model to identify fraud. Your model will produce predictions that can be interpreted as the probability of fraud. You will pass on the top 100 scoring cases to management for investigation. Assume that you have sufficient data to hold out a validation and test data set for model evaluation.
Which selection would represent a reasonable ordering of fit statistics (best to worst) for this situation?
Select one:
Response:
A) Misclassification rate, ROC index, ASE
B) R-square, AIC, K-S statistic
C) ASE, Lift for the top 10%, ROC index
D) ROC index, ASE, misclassification rate
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: D | Question # 5 Answer: D |
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