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SASInstitute A00-485 Exam Syllabus Topics:

SectionObjectives
Model Evaluation and Interpretation- Interpreting model outputs and reports
- Assessing model performance
Data Preparation and Exploration in SAS Viya- Loading and preparing data for Visual Statistics
- Exploratory data analysis and visualization
Predictive Modeling Fundamentals- Model selection and comparison techniques
- Regression modeling concepts
  • 1. Logistic regression
    • 2. Linear regression
      Machine Learning Methods in Visual Statistics- Decision trees and random forests concepts
      - Clustering techniques

      SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

      1. Refer to the exhibit:

      Which is the modeling approach that should be used when fitting the Target Gift Amount variable?

      A) Logistic regression model.
      B) Linear regression model with Interaction effects.
      C) Generalized linear model with a Poisson distribution and Identity link.
      D) Generalized linear model with a Normal distribution and Log Link.


      2. What information is conveyed by a Summary bar in model assessment?

      A) The standard deviation of the predictor variables
      B) The distribution of residuals in the model
      C) The performance metrics of the model, such as AUC and KS Statistic
      D) The summary statistics of the response variable


      3. When building a Generalized Linear Model in SAS Visual Statistics, which link function is available?

      A) Log
      B) Negative Binomial
      C) Poisson
      D) Gaussian


      4. What does a ROC chart help assess in model comparison?

      A) The trade-off between true positives and false positives at different thresholds
      B) The correlation between predictor variables
      C) The distribution of residuals in the models
      D) The stability of model predictions


      5. What is the primary purpose of assigning variable roles in linear regression?

      A) To specify which variables are categorical and which are continuous
      B) To indicate which variables are predictors and which are responses
      C) To determine the order in which variables are entered into the model
      D) To determine the level of significance for each variable


      Solutions:

      Question # 1
      Answer: D
      Question # 2
      Answer: C
      Question # 3
      Answer: A
      Question # 4
      Answer: A
      Question # 5
      Answer: A

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