A00-485 exam dumps

SASInstitute A00-485 Value Package

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  • Exam Code: A00-485
  • Exam Name: Modeling Using SAS Visual Statistics
  • No. of Questions: 190 Questions and Answers
  • Updated: Aug 06, 2026

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SASInstitute A00-485 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Model Comparison and Scoring9%- Apply models to score new data
- Compare multiple models using fit statistics
Topic 2: Building and Assessing Segmentation Models28%- Analyze and interpret cluster results
- Perform supervised segmentation using decision trees
- Perform unsupervised segmentation using cluster analysis
- Assess and interpret decision tree performance
Topic 3: Building and Assessing Regression-type Models41%- Perform linear regression modeling
- Perform generalized additive modeling
- Explain concepts of linear models
- Perform nonparametric logistic regression modeling
- Assess model fit and diagnostics
- Perform generalized linear regression modeling
Topic 4: SAS Visual Statistics Cross-functional Tasks22%- Perform model validation
- Use interactive group-by functionality
- Filter data used for a model
- Prepare data using SAS Visual Analytics

SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. What do cluster properties refer to in the context of cluster analysis?

A) A measure of data point centrality
B) Descriptive statistics of individual data points
C) The number of clusters in the analysis
D) Characteristics shared by data points within a cluster


2. The Leaf size property within a decision tree is changed from 5 to 10 and no other stopping rules were met.
How will the tree change?

A) The tree will be simpler.
B) The tree will be more complex.
C) The tree will train more slowly.
D) The tree will be harder to interpret.


3. When filtering data for a model in SAS Visual Analytics, what can you do to exclude selections and filter data?

A) Specify exclusion criteria in the data source properties
B) Define a filter condition using the interactive filter pane
C) Use the exclude option when setting up a filter
D) Apply a data filter on the visualization


4. Prior to fitting a regression model, data binning of a continuous effect should be used for what purpose?

A) Reduce the cardinality of a continuous effect.
B) Reduce the impact of minor observation errors.
C) Improve the accuracy of your predictions.
D) Gain information due to discretization.


5. Refer to the exhibit:

Using the lift chart above to evaluate a decision tree model where the event level is Purchase, what is the expected performance of the model for the best 20% of cases predicted?

A) About 1.1 times better than a random sample of the same size
B) About 1.25 times better than a random sample of the same size
C) About 4 times better than a random sample of the same size
D) About 1.5 times better than a random sample of the same size


Solutions:

Question # 1
Answer: D
Question # 2
Answer: A
Question # 3
Answer: A,B,C,D
Question # 4
Answer: B
Question # 5
Answer: D

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