This course is designed for SAS professionals who use SAS/STAT software to conduct and interpret complex statistical data analysis.
Statisticians, researchers, and business analysts who use SAS programming to generate analyses using either continuous or categorical response (dependent) variables; as well as modelers and analysts who need to build predictive models, particularly models from the banking, financial services, direct marketing, insurance and telecommunications industries
This course is designed for SAS professionals who use SAS/STAT software to conduct and interpret complex statistical data analysis. It covers analysis of variance, linear and logistic regression, preparing inputs for predictive models, and measuring model performance.
Led by an expert instructor who can virtually look over your shoulder. Discuss, share, exchange ideas with students from different countries
Classroom training options include courses offered in our regional training centers or via our Live Web classroom.
Taught by certified instructors at high-tech facilities across the country
Before attending this course, you should have completed the equivalent of an undergraduate course in statistics covering p-values, hypothesis testing, analysis of variance, and regression.
Predictive Modeling Using Logistic Regression
Course Overview and Review of Concepts
ANOVA and Regression
More Complex Linear Models
Model Building and Effect Selection
Model Post-Fitting for Inference
Model Building and Scoring for Prediction
Categorical Data Analysis
Fitting the Model
Preparing the Input Variables