Business Knowledge Series course
Presented by Chip Wells, Ph.D., Manager, Analytical Education, Education Division, SAS; or Mike Patetta, Analytical Training Consultant, Education Division, SAS
This advanced course covers predictive hazard modeling for customer history data. Designed for analysts, the course uses SAS Enterprise Miner to illustrate survival data mining methods and their practical implementation.
Learn how to
- build models for time-dependent outcomes derived from customer event histories
- account for competing risks, time-dependent covariates, right censoring, and left truncation
- compute the expected value of the remaining time until an event
- evaluate the predictive performance of the model
- score new customers.
Who should attend
Predictive modelers, data analysts, statisticians, econometricians, model validators, and data scientists
Before attending this course, you should
- have a basic understanding of survival analysis
- have experience with predictive modeling, particularly with logistic regression
- be familiar with statistical concepts such as random variables, probability distributions, and parameter estimation.
SAS programming experience is helpful but not mandatory.
This course addresses SAS Enterprise Miner software.