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SASInstitute A00-240 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Linear Regression20%- Model Selection and Diagnostics
  • 1. Assess model validity
  • 2. Conduct residual and diagnostic analysis
  • 3. Perform model selection using REG or GLMSELECT
- Interpret Regression Results
  • 1. Evaluate parameter estimates
  • 2. Interpret REG, PLM and GLM output
- Build Regression Models
  • 1. Fit multiple linear regression models
  • 2. Use REG and GLM procedures
Topic 2: ANOVA10%- ANOVA Analysis
  • 1. Analyze differences between population means using GLM and TTEST procedures
  • 2. Evaluate treatment effects
  • 3. Perform post hoc tests
  • 4. Detect and analyze factor interactions
- ANOVA Concepts and Assumptions
  • 1. Identify appropriate ANOVA methods
  • 2. Verify ANOVA assumptions
Topic 3: Logistic Regression25%- Interpret and Deploy Models
  • 1. Interpret LOGISTIC procedure output
  • 2. Score new data sets using LOGISTIC and PLM procedures
- Develop Logistic Models
  • 1. Perform logistic regression using the LOGISTIC procedure
  • 2. Optimize model performance through input selection
Topic 4: Prepare Inputs for Predictive Model Performance20%- Variable Engineering and Screening
  • 1. Screen variables for irrelevance
  • 2. Improve predictive power of categorical variables
  • 3. Use empirical logit plots for nonlinearity detection
  • 4. Identify nonlinear associations using CORR procedure
- Data Preparation
  • 1. Use loops, arrays, functions and conditional statements
  • 2. Identify challenges in preparing model input data
  • 3. Manipulate data using DATA step programming
Topic 5: Measure Model Performance25%- Model Assessment
  • 1. Assess classifier performance using confusion matrices
  • 2. Apply principles of honest assessment
- Validation and Selection
  • 1. Compare and select predictive models
  • 2. Perform model validation using training and validation data
- Decision Optimization
  • 1. Evaluate scoring strategies
  • 2. Establish effective decision cutoff values
- Performance Visualization
  • 1. Create and interpret gains charts
  • 2. Create and interpret lift charts
  • 3. Create and interpret ROC charts

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SASInstitute SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Credential Sample Questions (Q83-Q88):

NEW QUESTION # 83
Which of the following describes a concordant pair of observations in the LOGISTIC procedure?

Answer: C

Explanation:
Explanation


NEW QUESTION # 84
Given the following SAS data set TEST:

Which SAS program is NOT a correct way to create dummy variables?

Answer: B


NEW QUESTION # 85
The Model SS in a multiple linear regression model is equal to:

Answer: C


NEW QUESTION # 86
Refer to the following odds ratio table:

What is a correct interpretation of the estimate?

Answer: C


NEW QUESTION # 87
A financial services manager wants to assess the probability that certain clients will default on their Home Equity Line of Credit (HELOC). A former employee left the code listed below.

The training data set is named HELOC, while a similar data set of more recent clients is named RECENT_HELOC. Which SAS data steps will calculate the predicted probability of default on recent clients?
(Choose two.)

Answer: A,B


NEW QUESTION # 88
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