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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Model Evaluation and Interpretation | - Interpreting model outputs and reports - Assessing model performance |
| Machine Learning Methods in Visual Statistics | - Clustering techniques - Decision trees and random forests concepts |
| Data Preparation and Exploration in SAS Viya | - Exploratory data analysis and visualization - Loading and preparing data for Visual Statistics |
| Predictive Modeling Fundamentals | - Regression modeling concepts
|
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
1. Refer to the exhibit:
A retailer wants to use a decision tree to select one segment to mail 35,000 coupons to existing customers for a new line of organic products.
Assuming that customers who have purchased organic products in the past are likely to want new organic products in the future, select the single best Leaf ID for the mailing.
A) 18
B) 17
C) 15
D) 12
2. When performing a logistic regression in SAS Visual Statistics, the default prediction cutoff is .50. If you increase the cutoff to .80 then derive predicted values, which statement is the expected outcome?
A) The predicted events decrease and the predicted probabilities remain unchanged.
B) The predicted events remain unchanged and the predicted probabilities decrease.
C) The predicted events remain unchanged and the predicted probabilities increase.
D) The predicted events increase and the predicted probabilities remain unchanged.
3. What do cluster properties refer to in the context of cluster analysis?
A) A measure of data point centrality
B) The number of clusters in the analysis
C) Characteristics shared by data points within a cluster
D) Descriptive statistics of individual data points
4. How can you apply filters to both visualization and data source in SAS Visual Analytics?
A) Define filters directly in the data source properties
B) Use the toolbar options to filter the visualization
C) Use the filter pane to apply filters to the visualization
D) Apply filters using the interactive filter dialog in the visualization
5. When building a cluster analysis in SAS Visual Statistics, which of the following algorithms is commonly used for partitioning data into clusters?
A) K-means
B) Principal Component Analysis (PCA)
C) Decision Tree
D) Linear Regression
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: A,B,C,D | Question # 5 Answer: A |
