MITx course builds a systematic approach to understanding the uncertain
6.041x shows learners how to use probability to make scientifically sound predictions under uncertainty.
Sara Sezun and Steve Carson
Office of Digital Learning
January 29, 2013
Many aspects of our personal and professional lives are fraught with uncertainty. Should we invest in the stock market now, or wait? How reliable are the GPS readings on a smartphone? What is the likelihood that a medical treatment will be effective? Through the new MITx course 6.041x (Introduction to Probability – The Science of Uncertainty), MIT professors John Tsitsiklis and Patrick Jaillet share the probabilistic models used to analyze these and many other uncertain situations.
While the course was developed in the Department of Electrical Engineering and Computer Science (EECS) over many decades, Tsitsiklis says the course is relevant to a much wider audience: “The class is targeted not just to EE (Electrical Engineering) students. For example, biologists need probability tools more and more.”
Tsitsiklis, the Clarence J Lebel Professor of Electrical Engineering, also describes his course’s approach as unique: “We’re more ambitious than the typical undergraduate probability class. We’re different from a class that gives an overview of problems and ideas … We aim to provide the crispest way of explaining the concepts.”
He explains that the ability to think probabilistically is a fundamental component of scientific literacy. Students in 6.041x will learn the models, skills, and tools that are the keys to analyzing data and making scientifically sound predictions under uncertainty. Read more.