Failure and Survival Data Analysis

Course Description

This course introduces both parametric and non-parametric statistical models for analysis of the failure and survival data - a critical topic in quantitative finance, econometrics, and biostatistics. Different censoring mechanisms will be discussed. The course will mainly cover Kaplan-Meier estimator for characterizing the distribution of the failure and survival data, non-parametric log-rank test for comparing multiple groups, and the accelerated failure time model and Cox regression model uncovering various predictor/explanatory variables to survival/failure. Applications to finance, economics and biomedicine will be illustrated. We have revised the course title and content to better suit our current graduate programs in Applied Mathematics and Statistics that have evolved substantially from our old forms. In our current program, students from many tracks, especially in statistics and in quantitative finance, need this updated course as a highly relevant and important elective. This same subject is generally referred to as `Survival data analysis’ in biostatistics, but `Failure data analysis’ in finance. This updated title will reflect the content of the course clearly for students from all tracks. 3 credits Grading Letter graded (A, A-, B+, etc.)

Code

AMS 588

Credits

3

Subject

AMS