Probabilistic Systems Analysis and Applied Probability
6.041 · Electrical Engineering and Computer Science · Undergraduate · Fall 2010
Prof. John Tsitsiklis
<p>Welcome to 6.041/6.431, a subject on the modeling and analysis of random phenomena and processes, including the basics of statistical inference. Nowadays, there is broad consensus that the ability to think probabilistically is a fundamental component of scientific literacy. For example:</p> <ul> <li>The concept of statistical significance (to be touched upon at the end of this course) is considered by the Financial Times as one of “The Ten Things Everyone Should Know About Science”.</li> <li…
The syllabus, on MIT OpenCourseWare
The full course — syllabus, assigned readings, problem sets, exams, and lecture notes — lives on OCW. These open the real thing:
Syllabus ↗
Course overview, grading, schedule
Readings ↗
The assigned reading list, session by session
Assignments ↗
Problem sets and projects
Full course on OCW ↗
Everything, including lecture materials
Attribution
Prof. John Tsitsiklis. 6.041 Probabilistic Systems Analysis and Applied Probability. Fall 2010. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: CC BY-NC-SA 4.0.
Course materials are © their authors and licensed CC BY-NC-SA 4.0. CurrMana links to the source and does not re-host them.