Reliability Data Collection and Analysis
This course provides students with an overview of methods and tools for collecting and analyzing data to estimate parameters of probabilistic models. While the fundamentals covered in the course are applicable to many domains of science and engineering, the focus will be risk and reliability applications. This course provides an overview of relevant foundational topics in probability and statistics (both Bayesian and classical) followed by a comprehensive coverage of specific inference and estimation techniques for different types of data such as field data and data collected from testing or under laboratory conditions. Also covered are cases involving ‘soft’ evidence (uncertain, partially applicable information, and expert opinion). Both parametric and non-parametric methods are explained. Also covered are methods for collecting and categorizing data from field observations and tests.