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SASInstitute A00-485 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Machine Learning Methods in Visual Statistics | - Clustering techniques - Decision trees and random forests concepts |
| Topic 2: Model Evaluation and Interpretation | - Assessing model performance - Interpreting model outputs and reports |
| Topic 3: Predictive Modeling Fundamentals | - Regression modeling concepts
|
| Topic 4: 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 are some properties that can be defined in a generalized linear regression model?
A) Distribution and link function
B) Residuals and intercept
C) Number of predictors
D) Coefficients and p-values
2. When building a Generalized Linear Model in SAS Visual Statistics, which link function is available?
A) Poisson
B) Negative Binomial
C) Log
D) Gaussian
3. When modeling binary outcomes in a generalized linear model, which distribution and link function combination is commonly used?
A) Exponential distribution with a square root link function
B) Poisson distribution with a log link function
C) Normal distribution with an identity link function
D) Binomial distribution with a logit link function
4. When investigating leaf nodes in a decision tree, what does it reveal about the data?
A) The statistical significance of each leaf node
B) The feature values associated with each leaf node
C) The decision rules leading to each leaf node
D) The class labels assigned to each leaf node
5. Which SAS tool is most suitable for managing explorations and visualizations in a business intelligence context?
A) SAS Enterprise Miner
B) SAS Visual Data Builder
C) SAS Studio
D) SAS Enterprise Guide
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: C | Question # 3 Answer: D | Question # 4 Answer: B,C,D | Question # 5 Answer: B |
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