Event Details
Anyone involved in risk analysis, especially those considering probabilistic risk assessments (PRA), should have a basic understanding of statistics. Unfortunately, most books and courses quickly get lost in detail most engineers will not find useful. This short course introduces important statistical concepts in a way that engineers can understand – that they are just models of data generating processes. We will aim to demystify topics like probability distributions and confidence intervals by unpacking how statistical models generate data.
Attendees will receive 2 Professional Development Hours (PDH) upon completion.
Course Objectives
Understand what statistical models can do and how they do it, including prediction, input/feature importance, and uncertainty quantification.
Who should attend?
Engineers or any other technical employee tasked with making risk-based decisions or otherwise see a practical use for statistical analysis (and eventually machine learning) in their work.
Meet the Instructor
Kevin J. Koning, PE
DTE Gas Principal Engineer-DIMP
Kevin first ran into how difficult statistics are for engineers while a graduate student research assistant working to quantify model uncertainty through Monte Carlo methods (he found statistics endlessly confusing). After that he worked as a consultant and professional engineer in Michigan, New York, and Illinois. He transitioned to more hands-on work rebuilding utility infrastructure at a municipal utility where he eventually became a department manager. He now works at DTE energy where his work in distribution integrity management and probabilistic risk assessment supports major renewal programs.
