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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Model Evaluation and Interpretation | - Interpreting model outputs and reports - Assessing model performance |
| Predictive Modeling Fundamentals | - Model selection and comparison techniques - Regression modeling concepts
|
| Machine Learning Methods in Visual Statistics | - Decision trees and random forests concepts - Clustering techniques |
| Data Preparation and Exploration in SAS Viya | - Loading and preparing data for Visual Statistics - Exploratory data analysis and visualization |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
1. What is meant by "informative missingness" in the context of linear regression?
A) Missing data that provides valuable information about the outcome
B) Missing data that is unrelated to the outcome variable
C) Missing data that is randomly distributed across observations
D) Missing data that leads to multicollinearity among predictors
2. You have a regression model effect that represents the total amount of sales. In addition to that, you would like to create a model effect that represents the average amount of sales.
Which option should you use?
A) Create an aggregated measure using the Sum aggregation of total amount of sales divided by the Sum aggregation of total amount of items sold.
B) Create a calculated item that divides total amount of sales by the total amount of items sold.
C) Create an aggregated measure using the Avg aggregation on total amount of sales.
D) Create a calculated item by duplicating the original model effect and changing its default aggregation to Average.
3. What is the primary benefit of exporting score code for model deployment?
A) It allows for model performance assessment on a test dataset.
B) It enables scoring of new data without the need for SAS Visual Statistics.
C) It automatically generates new predictor variables.
D) It provides insights into the distribution of predictor variables.
4. Which statement is true regarding the Cluster Analysis in SAS Visual Statistics?
A) You can derive a Cluster ID variable by right clicking on the Parallel Coordinates plot.
B) An observation can belong to more than one cluster.
C) Clusters may overlap in the Cluster Matrix plot.
D) SAS Visual Statistics creates a measure variable containing the cluster ID when you derive a Cluster ID variable.
5. When filtering data for a model in SAS Visual Analytics, what can you do to exclude selections and filter data?
A) Apply a data filter on the visualization
B) Define a filter condition using the interactive filter pane
C) Specify exclusion criteria in the data source properties
D) Use the exclude option when setting up a filter
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: A,B,C,D |







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