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SAS Statistical Business Analysis SAS9: Regression and Model
Last Updated: Oct 3, 2024
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99 Questions and Answers for the SAS A00-240 exam
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SAS Statistical Business Analysis SAS9: Regression and Model Syllabus
- Identify the potential challenges when preparing input data for a model/ Detect and analyze interactions between factors
- Model selection and validation using training and validation data/ Perform ANOVA post hoc test to evaluate treatment effect
- Establish effective decision cut-off values for scoring/ Fit a multiple linear regression model using the REG and GLM procedures
- Create and interpret graphs (ROC, lift, and gains charts) for model comparison and selection/ Use the REG or GLMSELECT procedure to perform model selection
- Screen variables for irrelevance and non-linear association using the CORR procedure/ Perform logistic regression with the LOGISTIC procedure
- Screen variables for non-linearity using empirical logit plots/ Score new data sets using the LOGISTIC and PLM procedures
- Apply the principles of honest assessment to model performance measurement/ Optimize model performance through input selection
- Analyze differences between population means using the GLM and TTEST procedures/ Assess classifier performance using the confusion matrix
- Assess the validity of a given regression model through the use of diagnostic and residual analysis/ Prepare Inputs for Predictive Model Performance
- Analyze the output of the REG, PLM, and GLM procedures for multiple linear regression models/ Improve the predictive power of categorical inputs