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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Preparation and Exploration in SAS Viya | - Loading and preparing data for Visual Statistics - Exploratory data analysis and visualization |
| Topic 2: Predictive Modeling Fundamentals | - Model selection and comparison techniques - Regression modeling concepts
|
| Topic 3: Machine Learning Methods in Visual Statistics | - Clustering techniques - Decision trees and random forests concepts |
| Topic 4: Model Evaluation and Interpretation | - Assessing model performance - Interpreting model outputs and reports |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
What is the purpose of reviewing Measure Details when preparing data for a model?
- A. To determine the aggregation method for measures
- B. To check data types and formats of the measures
- C. To identify missing values in the measures
- D. To understand the level of measurement for each variable
Correct Answer: B,D 🗳️
How is a multinomial response variable used in SAS Visual Statistics when building a logistic regression model?
- A. It is used as an event variable.
- B. It is not used in logistic regression modeling.
- C. It is used as a predictor variable.
- D. It is used to define the outcome categories.
Correct Answer: D 🗳️
In generalized linear models, what is the purpose of the link function?
- A. To determine the distribution of the response variable
- B. To specify the relationship between the predictor and response variables
- C. To calculate the p-values of predictor variables
- D. To adjust the model for multicollinearity
Correct Answer: B 🗳️
Refer to the exhibit from SAS Visual Statistics:
What can be concluded from the lift plot shown in the exhibit?
- A. The 20% of cases with the lowest predicted probability of the modeled event level is predicted to capture 2.75 times as many events as a random sample of 20%.
- B. The 20% of cases with the highest predicted probability of the modeled event level is expected to capture 2.75 times as many events as a random sample of the same size.
- C. The response rate for the best 20% is predicted to be 2.75 times greater than the sample fitted in the model.
- D. The response rate for the best 20% is predicted to increase 5 times under the fitted model.
Correct Answer: B 🗳️
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 provides insights into the distribution of predictor variables.
- C. It automatically generates new predictor variables.
- D. It enables scoring of new data without the need for SAS Visual Statistics.
Correct Answer: D 🗳️
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