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SASInstitute A00-485 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Preparation and Exploration20%- Data quality
- Data exploration using SAS Visual Statistics
- Importing data
Topic 2: Building Predictive Models40%- Gradient boosting
- Neural networks
- Decision trees
- Regression models
Topic 3: Model Assessment and Selection20%- Model fit statistics
- ROC and Lift curves
- Model comparison
Topic 4: Scoring and Deployment20%- Model scoring
- Model deployment

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

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

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

In linear regression modeling, what roles are typically assigned to variables?

  • A. Input, Target, and Nominal
  • B. Predictor, Response, and Interaction
  • C. Dependent, Independent, and Categorical
  • D. Intercept, Slope, and Error
Answer: C

What is the purpose of implementing score code generated by SAS Visual Statistics?

  • A. To evaluate the performance of the scoring code
  • B. To calculate the p-values of predictor variables
  • C. To apply the trained model to new data for predictions
  • D. To assess the distribution of residuals in the model
Answer: C

What is the primary goal of linear models in statistical modeling?

  • A. To predict categorical outcomes
  • B. To capture non-linear relationships in data
  • C. To classify data into distinct groups
  • D. To establish a linear relationship between variables
Answer: D

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. Apply group-by modeling to multiple measures simultaneously
  • C. Create subgroups within the group-by variable
  • D. Dynamically change the group-by variable during analysis
Answer: A,D

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