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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Predictive Modeling Fundamentals | - Regression modeling concepts
|
| Data Preparation and Exploration in SAS Viya | - Loading and preparing data for Visual Statistics - Exploratory data analysis and visualization |
| 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 |
SASInstitute Modeling Using SAS Visual Statistics Sample Questions:
Question 1
How can score code be implemented to score new data using SAS Enterprise Miner?
A. By manually executing the code in a command-line interface
B. By importing the code into SAS Data Integration Studio
C. By creating a scoring node in a SAS Enterprise Miner process flow
D. By pasting the code into a web browser
Question 2
How does SAS Data Integration Studio facilitate scoring new data using exported score code?
A. By providing a visual interface for connecting to external data sources
B. By generating score code automatically during ETL processes
C. By enabling the scheduling of batch scoring jobs
D. By automatically tuning hyperparameters for scoring
Question 3
What is the primary purpose of modeling effects in linear regression?
A. To capture the relationship between predictors and the response variable
B. To identify outliers in the data
C. To assess multicollinearity among predictors
D. To calculate the p-values of the predictors
Question 4
Refer to the exhibit:
An economist is predicting demand using a linear regression model.
If all of the effect variables equal 1, what is the predicted demand?
A. 362.415133
B. 352.405432
C. 352.415433
D. 352.454433
Question 5
What is the purpose of applying a prediction cut-off in model assessment?
A. To determine the optimal threshold for classifying outcomes
B. To calculate the p-values of predictor variables
C. To divide the dataset into training and testing sets
D. To identify influential data points in the dataset
Solutions:
| Question 1 Answer: C | Question 2 Answer: B,C | Question 3 Answer: A | Question 4 Answer: C | Question 5 Answer: A |
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