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Exam Code: A00-485
Exam Name: Modeling Using SAS Visual Statistics
Updated: Sep 20, 2026
Q & A: 190 Questions and Answers
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Preparation and Exploration | 20% | - Data quality - Importing data - Data exploration using SAS Visual Statistics |
| Topic 2: Model Assessment and Selection | 20% | - ROC and Lift curves - Model comparison - Model fit statistics |
| Topic 3: Scoring and Deployment | 20% | - Model deployment - Model scoring |
| Topic 4: Building Predictive Models | 40% | - Regression models - Neural networks - Decision trees - Gradient boosting |
Which statement is true for negative binomial and Poisson regression models?
Correct Answer: A 🗳️
Which equation does NOT represent a linear model? Note: bi are parameters and Xi are variables.
Correct Answer: D 🗳️
You have a regression model effect that represents the total amount of sales. In addition to that, you would like to create a model effect that represents the average amount of sales.
Which option should you use?
Correct Answer: D 🗳️
In the context of linear regression, what does the term "linearity" refer to?
Correct Answer: B 🗳️
What is the purpose of implementing score code generated by SAS Visual Statistics?
Correct Answer: B 🗳️
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