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SASInstitute A00-485 Exam Syllabus Topics:

SectionObjectives
Machine Learning Methods in Visual Statistics- Clustering techniques
- Decision trees and random forests concepts
Predictive Modeling Fundamentals- Regression modeling concepts
  • 1. Linear regression
    • 2. Logistic regression
      - Model selection and comparison techniques
      Data Preparation and Exploration in SAS Viya- Exploratory data analysis and visualization
      - Loading and preparing data for Visual Statistics
      Model Evaluation and Interpretation- Assessing model performance
      - Interpreting model outputs and reports

      SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

      Question #1

      Your data contains a column for Country that contains 350 unique values. There are multiple entries for some countries (Japan, JPN, japan, etc.). You want a unique value for each country.
      Which is the most efficient way to correct inconsistent values?

      • A. Create a Custom Category that combines all the variations of a country into one.
      • B. Create a data source filter to suppress the incorrect variations of a country.
      • C. Create a calculated item using a Boolean IF...ELSE statement that changes the incorrect variations.
      • D. Create a visualization filter to suppress the incorrect variations of a country.
      Reveal Solution  Discussion  0

      Correct Answer: A  🗳️

      Question #2

      What does the interactive group-by feature in SAS Visual Analytics allow you to do?

      • A. Interactively explore different levels of the group-by variable
      • B. Dynamically change the group-by variable during analysis
      • C. Create subgroups within the group-by variable
      • D. Apply group-by modeling to multiple measures simultaneously
      Reveal Solution  Discussion  0

      Correct Answer: A,B  🗳️

      Question #3

      Refer to the exhibit from a linear regression model in SAS Visual Statistics.

      Based on the table above and assuming a significance level of 0.05, what can be concluded about the linear regression model?

      • A. RestPulse is a significant predictor of the response.
      • B. For one one-unit increase in RunTime, there is an expected increase in the response of 2.6287.
      • C. For a .03696 unit decrease in RunPulse, there is an expected one-unit increase in the response.
      • D. The Intercept is an important predictor of the response.
      Reveal Solution  Discussion  0

      Correct Answer: B  🗳️

      Question #4

      How can you interpret the impurity measures in an icicle plot of a decision tree?

      • A. Higher impurity indicates better separation of classes.
      • B. Impurity measures represent the number of data points in a leaf node.
      • C. Impurity measures are irrelevant in decision tree analysis.
      • D. Lower impurity implies more homogeneity within a leaf node.
      Reveal Solution  Discussion  0

      Correct Answer: D  🗳️

      Question #5

      How is a multinomial response variable used in SAS Visual Statistics when building a logistic regression model?

      • A. It is used as a predictor variable.
      • B. It is used to define the outcome categories.
      • C. It is not used in logistic regression modeling.
      • D. It is used as an event variable.
      Reveal Solution  Discussion  0

      Correct Answer: B  🗳️

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