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SASInstitute Modeling Using SAS Visual Statistics : A00-485
- Exam Code: A00-485
- Exam Name: Modeling Using SAS Visual Statistics
- Updated: Oct 10, 2026 Q & A: 190 Questions and Answers
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About SASInstitute A00-485 Exam
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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Preparation and Exploration | 20% | - Data exploration using SAS Visual Statistics - Importing data - Data quality |
| Topic 2: Model Assessment and Selection | 20% | - Model fit statistics - ROC and Lift curves - Model comparison |
| Topic 3: Scoring and Deployment | 20% | - Model scoring - Model deployment |
| Topic 4: Building Predictive Models | 40% | - Regression models - Decision trees - Gradient boosting - Neural networks |
Frequently Asked Questions About SASInstitute Modeling Using SAS Visual Statistics
If you are purchasing for a company, take all three versions of SASInstitute Modeling Using SAS Visual Statistics, since different employees study differently. If you are buying for yourself, pick the single version that matches your habits: the PDF for printing and writing on paper, the PC test engine for simulation tests with scored feedback, or the APP online engine for cross-platform use with offline support.
A00-485 requires 68 to pass, and the official exam fee is USD 180. Remember that a retake means paying that fee again, which is why focused preparation matters.
The A00-485 exam contains 60 questions within 110 minutes minutes. Rehearsing under the same limit on the PracticeTorrent engine builds calm, automatic pacing.
IT certification exams are not cheap, and failing usually means paying the full fee a second time plus losing the hours you already invested. Serious preparation with SASInstitute Modeling Using SAS Visual Statistics exists precisely to prevent that double cost: study the 190 verified questions well, and you give yourself a strong, realistic chance of passing the A00-485 exam the first time.
The package includes 190 practice questions for the A00-485 exam, all with verified answers, in PDF, PC test engine, and APP online engine versions.
- Building Predictive Models (40%)
- Data Preparation and Exploration (20%)
- Model Assessment and Selection (20%)
Spend your hours where the weights are highest.
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
Question #1
When performing a logistic regression in SAS Visual Statistics, the default prediction cutoff is .50. If you increase the cutoff to .80 then derive predicted values, which statement is the expected outcome?
- A. The predicted events remain unchanged and the predicted probabilities increase.
- B. The predicted events remain unchanged and the predicted probabilities decrease.
- C. The predicted events increase and the predicted probabilities remain unchanged.
- D. The predicted events decrease and the predicted probabilities remain unchanged.
Correct Answer: D 🗳️
Question #2
Given an Influence Plot generated in a Linear Regression within SAS Visual Statistics, which diagnostic can be used to quantify leverage?
- A. Likelihood Displacement
- B. AIC
- C. Concordance
- D. Adjusted R-Squared
Correct Answer: A 🗳️
Question #3
You perform a logistic regression on a multinomial response variable in SAS Visual Statistics that has 3 levels: Small, Medium, Large. "Large" is specified as the event.
Which statement is true?
- A. The other levels are offset to account for exposure.
- B. A multinomial logistic regression is performed.
- C. The other levels are grouped into one non-event.
- D. An ordinal logistic regression is performed.
Correct Answer: C 🗳️
Question #4
When modeling binary outcomes in a generalized linear model, which distribution and link function combination is commonly used?
- A. Poisson distribution with a log link function
- B. Exponential distribution with a square root link function
- C. Binomial distribution with a logit link function
- D. Normal distribution with an identity link function
Correct Answer: C 🗳️
Question #5
In decision tree analysis, what is typically found on the y-axis of an icicle plot?
- A. Class labels
- B. Depth of the tree
- C. Feature values
- D. Impurity measures
Correct Answer: A,B,C 🗳️
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