Exam Name: Modeling Using SAS Visual Statistics
Certification Provider: SASInstitute
Corresponding Certification: SASInstitute Certification
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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Model Assessment and Selection | 20% | - Model comparison - Model fit statistics - ROC and Lift curves |
| Topic 2: Scoring and Deployment | 20% | - Model deployment - Model scoring |
| Topic 3: Data Preparation and Exploration | 20% | - Importing data - Data quality - Data exploration using SAS Visual Statistics |
| Topic 4: Building Predictive Models | 40% | - Neural networks - Regression models - Decision trees - Gradient boosting |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
What is the primary purpose of reviewing the residual plot in linear regression analysis?
- A. To detect outliers in the predictor variables
- B. To determine the p-value associated with the response variable
- C. To assess the linearity assumption and identify potential issues
- D. To calculate the coefficient of determination (R-squared)
Correct Answer: C 🗳️
What properties can be assigned when comparing models in SAS Visual Statistics?
- A. The number of observations in the dataset
- B. The learning rate for gradient boosting models
- C. The variables to include in the model comparison
- D. The color scheme for visualization
Correct Answer: C 🗳️
When investigating leaf nodes in a decision tree, what does it reveal about the data?
- A. The statistical significance of each leaf node
- B. The decision rules leading to each leaf node
- C. The feature values associated with each leaf node
- D. The class labels assigned to each leaf node
Correct Answer: B,C,D 🗳️
Which statement is true regarding model comparison within SAS Visual Statistics?
- A. A linear regression and a generalized linear model cannot be compared.
- B. Two cluster analyses cannot be compared if they have different initial seed assignments.
- C. A logistic regression and a decision tree cannot be compared.
- D. Two generalized linear models cannot be compared if they use different underlying distributions.
Correct Answer: B 🗳️
Refer to the exhibits:
An analyst is evaluating which model to use.
What changed from Comparison 1 to Comparison 2 to select a different champion model?
- A. Misclassification was used instead of Cumulative Lift
- B. Analyst clicked on Model 2 to highlight it
- C. Prediction Cutoff reduced from .5 to .19
- D. Percentile changed from 5th percentile to 40th percentile
Correct Answer: D 🗳️
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