The tools of probability theory, and of the related field of statistical …
The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management. This resource is a companion site to 6.041SC Probabilistic Systems Analysis and Applied Probability. It covers the same content, using videos developed for an edX version of the course.
Welcome to 6.041/6.431, a subject on the modeling and analysis of random …
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:
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". A recent Scientific American article argues that statistical literacy is crucial in making health-related decisions. Finally, an article in the New York Times identifies statistical data analysis as an upcoming profession, valuable everywhere, from Google and Netflix to the Office of Management and Budget.
The aim of this class is to introduce the relevant models, skills, and tools, by combining mathematics with conceptual understanding and intuition.
This course introduces students to the modeling, quantification, and analysis of uncertainty. …
This course introduces students to the modeling, quantification, and analysis of uncertainty. The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management. Course Format
This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:
Lecture Videos by MIT Professor John Tsitsiklis Lecture Slides and Readings Recitation Problems and Solutions Recitation Help Videos by MIT Teaching Assistants Tutorial Problems and Solutions Tutorial Help Videos by MIT Teaching Assistants Problem Sets with Solutions Exams with Solutions
Related Resource
A complementary resource, Introduction to Probability, is provided by the videos developed for an EdX version of 6.041. These videos cover more or less the same content, in somewhat different order, and in somewhat more detail than the videotaped live lectures.
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