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SASInstitute A00-255 Exam Overview:
| Certification Vendor: | SASInstitute |
|---|---|
| Exam Name: | SAS Predictive Modeling Using SAS Enterprise Miner 14 |
| Exam Number: | A00-255 |
| Passing Score: | 725 (scale 200–1000) |
| Exam Format: | Performance-based, Multiple choice, Short answer |
| Related Certifications: | SAS Certified Advanced Analytics Professional |
| Real Exam Qty: | 55–60 |
| Exam Price: | $250 USD |
| Exam Duration: | 165 minutes |
| Available Languages: | English |
| Certificate Validity Period: | Valid indefinitely once earned |
| Recommended Training: | SAS Enterprise Miner Training Courses |
| Exam Registration: | Pearson VUE Registration SAS Certification Registration |
| Sample Questions: | SASInstitute A00-255 Sample Questions |
| Exam Way: | Online proctored or onsite at Pearson VUE test centers |
| Pre Condition: | Recommended: experience with SAS Enterprise Miner, data mining and predictive modeling concepts; no mandatory prerequisites |
| Official Syllabus URL: | https://www.sas.com/en_us/certification/credentials/advanced-analytics/predictive-modeler-14.html |
SASInstitute A00-255 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Predictive Model Assessment and Implementation | 25–30% | - Evaluate performance via profit/loss and comparison - Adjust for oversampling and sampling methods - Score and deploy models - Apply appropriate fit statistics |
| Topic 2: Building Predictive Models | 35–40% | - Understand predictive modeling concepts - Build models using decision trees - Build models using neural networks - Build models using regression techniques |
| Topic 3: Data Sources | 20–25% | - Create data sources from SAS tables - Modify and prepare source data for modeling - Explore and assess data sources |
| Topic 4: Pattern Analysis | 10–15% | - Interpret pattern discovery results - Identify clusters and segments |
SASInstitute SAS Predictive Modeling Using SAS Enterprise Miner 14 Sample Questions:
Question 1
If we were to add a Transformation node, what would be the default transformation for interval inputs for the present scenario?
Response:
A. Maximum Correlation
B. Maximum Normal
C. Optimal
D. none of the above
Question 2
Perform these tasks in SAS Enterprise Miner:
- Use the Regression node to build another regression model with TARGET as the dependent variable and all other input variables as independent variables (main effects only).
- Configure the regression model to use Stepwise for Selection Model and Validation Error for Selection Criteri a. Do not change any other property for the regression model.
Which of the following variable(s) is (are) statistically significant at the 5% level in the selected model?
Response:
A. IMP_TLOpen24Pct
B. TLDel3060Cnt24
C. all of the above
D. TLTimeFirst
Question 3
In SAS Enterprise Miner's Decision Tree node, which of the following types of target variable can be used?
Response:
A. binary
B. nominal with any number of categories
C. all of the above
D. interval
Question 4
The number of neurons in this Neural Network model is which of the following:
Response:
A. 1
B. 4 or more
C. 2
D. 3
Question 5
What is the kurtosis value for the variable TLDel60Cnt24?
Response:
A. between 14 and 16.99
B. less than 10
C. between 10 and 13.99
D. 17 or higher
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: C | Question 4 Answer: A | Question 5 Answer: A |
By Moses
