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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Building and Assessing Segmentation Models | 28% | - Analyze and interpret cluster results - Perform supervised segmentation using decision trees - Perform unsupervised segmentation using cluster analysis - Assess and interpret decision tree performance |
| Topic 2: Model Comparison and Scoring | 9% | - Apply models to score new data - Compare multiple models using fit statistics |
| Topic 3: SAS Visual Statistics Cross-functional Tasks | 22% | - Filter data used for a model - Perform model validation - Use interactive group-by functionality - Prepare data using SAS Visual Analytics |
| Topic 4: Building and Assessing Regression-type Models | 41% | - Perform nonparametric logistic regression modeling - Explain concepts of linear models - Perform generalized additive modeling - Perform generalized linear regression modeling - Perform linear regression modeling - Assess model fit and diagnostics |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
Given a scenario, what fit statistic can be used to select a champion model in model comparison?
- A. The R-squared value
- B. The AUC (Area Under the Curve)
- C. The p-value of the intercept term
- D. The learning rate of the model
Correct Answer: B 🗳️
How can score code be implemented to score new data using SAS Enterprise Miner?
- A. By importing the code into SAS Data Integration Studio
- B. By creating a scoring node in a SAS Enterprise Miner process flow
- C. By pasting the code into a web browser
- D. By manually executing the code in a command-line interface
Correct Answer: B 🗳️
What is unsupervised classification in the context of cluster analysis?
- A. Using a decision tree for data classification
- B. Creating a scatter plot of data points
- C. Assigning predefined labels to data points
- D. Grouping similar data points together without predefined labels
Correct Answer: D 🗳️
When examining the summary table for group-by processing, what information can you find?
- A. The mean value of the target variable for each group
- B. The number of observations in each group
- C. The distribution of the group-by variable
- D. The standard deviation of the target variable for each group
Correct Answer: A,B,D 🗳️
You would like to compare multiple models that you've built in SAS Visual Statistics.
Which parameters must be the same for all models being compared? (choose 3)
- A. Model Type
- B. Assessment Bins
- C. Data Source
- D. Link Function
- E. Event Level
- F. Response Variable
Correct Answer: C,E,F 🗳️
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