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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 |
| Real Exam Qty: | 55-60 |
| Certificate Validity Period: | No expiration |
| Exam Format: | Multiple-choice, Short-answer, Performance-based |
| Passing Score: | 725/1000 |
| Available Languages: | English |
| 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 Duration: | 165 minutes |
| 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. 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.
Consider the variable TLCnt03 in the selected model. Based on the model results, changing this variable by 1 unit will result in which of the following?
Response:
A) reduction of odds for TARGET=1 by 0.708
B) change of odds for TARGET=1 by a factor 0.3457
C) change of odds for TARGET=1 by a factor 0.708
D) reduction of odds for TARGET=1 by 0.3457
2. Refer to the graphs shown below. The graphs are from a study of response rate to a marketing campaign.
How much more likely are the top 20% of targeted respondents to purchase the product than a randomly selected sample?
Select one:
Response:
A) 25%
B) 30%
C) 60%
D) 140%
3. If the bank wanted to select the best model based on which model achieves the highest lift for the third decile in the validation data, then which of the following is the best model?
Response:
A) Decision Tree (3-way)
B) Decision Tree
C) Neural Network
D) Regression
4. Refer to the exhibit:
When the Explore button is selected in the graphic, what information will be displayed?
Select one:
Response:
A) Sample Properties, Sample Statistics, sample data for the selected variable, and a pie chart of the selected variable
B) Sample Properties, Sample Statistics for all variables, and sample data for all variables
C) Sample Properties, Sample Statistics, sample data for the selected variable, and a histogram of the data for the selected variable
D) Sample Properties, Sample Statistics, sample data with all variables and values, and a histogram of the data for the selected variable
5. 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 input variables being used by the Neural Network model is which of the following?
Response:
A) 16-20
B) 21 or more
C) less than or equal to 10
D) 11-15
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: A |
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