Course description

This course introduces students to probability theory and statistics and their applications in engineering and data science. Topics include random variables distributions and densities conditional expectations statistical sampling limit theorems and Markov chains. The goal of this course is to prepare students with knowledge of probability theory and statistical methods that are widely used in several engineering disciplines and modern data science.

Instructor

  • Gordon McKay Professor of Electrical Engineering and of Applied Mathematics, Harvard University

Associated Schools

  • Harvard Division of Continuing Education

  • Harvard Summer School

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