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Updated: Jul 29, 2026
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| Certification Vendor: | SAS Institute |
| Exam Name: | Modeling Using SAS Visual Statistics |
| Exam Number: | A00-485 |
| Certificate Validity Period: | 5 years |
| Exam Duration: | 110 minutes |
| Exam Price: | $120 USD |
| Available Languages: | English |
| Real Exam Qty: | 55-60 |
| Exam Format: | Multiple choice, Short answer |
| Passing Score: | 68% |
| Recommended Training: | SAS Visual Statistics in SAS Viya: Interactive Model Building Official Exam Content Guide |
| Exam Registration: | SAS Certification Portal Pearson VUE Registration |
| Sample Questions: | SASInstitute A00-485 Sample Questions |
| Exam Way: | Online proctored or in-person at Pearson VUE authorized test centers |
| Pre Condition: | No formal prerequisites; basic knowledge of statistics and SAS Viya interface recommended |
| Official Syllabus URL: | https://www.sas.com/en_my/certification/credentials/bi-analytics/modeling-using-visual-statistics.html |
| Section | Weight | Objectives |
|---|---|---|
| Building and Assessing Segmentation Models | 28% | - Perform supervised segmentation using decision trees - Analyze and interpret cluster results - Assess and interpret decision tree performance - Perform unsupervised segmentation using cluster analysis |
| Model Comparison and Scoring | 9% | - Compare multiple models using fit statistics - Apply models to score new data |
| SAS Visual Statistics Cross-functional Tasks | 22% | - Perform model validation - Prepare data using SAS Visual Analytics - Filter data used for a model - Use interactive group-by functionality |
| Building and Assessing Regression-type Models | 41% | - Perform linear regression modeling - Perform nonparametric logistic regression modeling - Perform generalized additive modeling - Explain concepts of linear models - Assess model fit and diagnostics - Perform generalized linear regression modeling |
1. What are some properties that can be defined in a linear regression model?
A) Confusion matrix and accuracy
B) Maximum depth and minimum leaf size
C) Coefficients, p-values, and R-squared
D) Learning rate and number of iterations
2. You want to fit a Poisson regression and use the log link function to predict skin cancer from weather, pollution, and demographic variables. Each row in the data is a geographic region.
The response, Melanoma, is stored as the number of melanoma skin cancer cases in each region.
Because some regions have many people and some have few, your data also includes a variable with the region population.
What is the best way to include population in this model?
A) Add Population as an effect.
B) Add the log of Population as an effect.
C) Add the log of Population as an offset.
D) Add Population as an offset.
3. In SAS Visual Statistics, how can you use a derived cluster ID variable in another visualization?
A) By linking it to a table in a database
B) By including it as a dimension in a new visualization
C) By embedding it within a scatter plot
D) By exporting it as a separate dataset
4. In logistic regression, which variable is typically designated as the "event" variable (binary)?
A) The predictor variable with the highest p-value
B) The intercept term in the model
C) The response variable indicating the event occurrence
D) The predictor variable with the lowest p-value
5. When would you typically use a linear regression model instead of a generalized linear model (GLM)?
A) When the dependent variable is binary
B) When there is no assumption of linearity in the data
C) When dealing with count data
D) When the goal is to model categorical outcomes
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: B |
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