ESD.86 -- Models, Data and Inference for Socio-Technical Systems
Course Description: 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. Enrollment limited to 25 students.

This class is at the Graduate level
Instructor: R. C. Larson, D. D. Frey
Prerequisites: ESD.83, 6.041 or permission of instructor

Insider's Wisdom

ESD.86 is an introductory subject required of all 1st-year ESD doctroal students. It does not aspire to be an advanced statistics subject. The 1st half of the subject is introduction to probabilistic modeling, and the 2nd half is focused on statistics.

This course is a good course for anyone that needs to have statistics and probability in their research toolbox. It is specifically designed for students that will USE statistics in their research as opposed to doing statistical research. For students interested in a foundation for statistical research 6.434J might be a better fit.

Back to Classes