SASInstitute A00-485 Q&A - in .pdf

  • Exam Code: A00-485
  • Exam Name: Modeling Using SAS Visual Statistics
  • Updated: Oct 04, 2026
  • Q & A: 190 Questions and Answers
  • PDF Price: $59.98
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SASInstitute A00-485 Q&A - Testing Engine

  • Exam Code: A00-485
  • Exam Name: Modeling Using SAS Visual Statistics
  • Updated: Oct 04, 2026
  • Q & A: 190 Questions and Answers
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SASInstitute A00-485 Exam Syllabus Topics:
SectionObjectives
Topic 1: Predictive Modeling Fundamentals- Regression modeling concepts
  • 1. Linear regression
    • 2. Logistic regression
      - Model selection and comparison techniques
      Topic 2: Model Evaluation and Interpretation- Interpreting model outputs and reports
      - Assessing model performance
      Topic 3: Data Preparation and Exploration in SAS Viya- Loading and preparing data for Visual Statistics
      - Exploratory data analysis and visualization
      Topic 4: Machine Learning Methods in Visual Statistics- Decision trees and random forests concepts
      - Clustering techniques
      SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
      Question #1

      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 the log of Population as an effect.
      • B. Add Population as an effect.
      • C. Add Population as an offset.
      • D. Add the log of Population as an offset.
      Reveal Solution  Discussion  0

      Correct Answer: D  🗳️

      Question #2

      Refer to the exhibit:

      How many predictor variables would be included in the score code produced by this model?

      • A. 5
      • B. 8
      • C. 7
      • D. 13
      Reveal Solution  Discussion  0

      Correct Answer: A  🗳️

      Question #3

      What are the roles that can be assigned in a generalized linear model (GLM)?

      • A. Target
      • B. Predictor
      • C. Offset
      • D. Intercept
      Reveal Solution  Discussion  0

      Correct Answer: A,B,C  🗳️

      Question #4

      When would you typically use a linear regression model instead of a generalized linear model (GLM)?

      • A. When the goal is to model categorical outcomes
      • B. When the dependent variable is binary
      • C. When there is no assumption of linearity in the data
      • D. When dealing with count data
      Reveal Solution  Discussion  0

      Correct Answer: C  🗳️

      Question #5

      You want to filter out certain observations to analyze their effect on the model.

      Which windows will achieve this? (Choose two.)

      • A. Influence Plot
      • B. Assessment
      • C. Residual Plot
      • D. Fit Summary
      Reveal Solution  Discussion  0

      Correct Answer: A,C  🗳️

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