Predictive Modeling with Logistic Regression using SAS

This course covers predictive modeling with SAS/STAT software, with an emphasis on the LOGISTIC process. The course covers selecting variables and interactions, recoding categorical variable based on smooth weight of evidence and assessing models. It also discusses how to treat missing values and use efficiency techniques for large data sets. Logistic regression is used to model the behavior of an individual as a function od inputs. You also learn how to create effect and odds ratio plots, deal with missing data, and manage multicollinearity. Additionally, you will learn how to evaluate model performance and compare models.