ESD.86J Models, Data and Inference for Socio-Technical Systems
Use data and systems knowledge to build models of complex socio-technical systems for improved system design and decision-making. Enhance model-building skills, including: review and extension of functions of random variables, Poisson processes, and Markov processes. Move from applied probability to statistics via Chi-squared t and f tests, derived as functions of random variables. Review classical statistics, hypothesis tests, regression, correlation and causation, simple data mining techniques, and Bayesian vs. classical statistics. Class project.
Lecture occurs 10:30 AM to 12:00 PM on Mondays and Wednesdays in E51-372.
This class counts for a total of 12 credits. This is a graduate-level class.
In the Spring 2015 Subject Evaluations, ESD.86J was rated 5.4 out of 7.0. You can find more information at the http://www.google.com/search?&q=MIT+%2B+ESD.86&btnG=Google+Search&inurl=https site.
© Copyright 2015 Yasyf Mohamedali