Statistics 110: Probability

Harvard, , Prof. Joe Blitzstein

Updated On 02 Feb, 19

Overview

This course is an introduction to probability as a language and set of tools for understanding statistics, science, risk, and randomness. The ideas and methods are useful in statistics, science, engineering, economics, finance, and everyday life. Topics include the following. Basics: sample spaces and events, conditioning, Bayes' Theorem. Random variables and their distributions: distributions, moment generating functions, expectation, variance, covariance, correlation, conditional expectation. Univariate distributions: Normal, t, Binomial, Negative Binomial, Poisson, Beta, Gamma. Multivariate distributions: joint, conditional, and marginal distributions, independence, transformations, Multinomial, Multivariate Normal. Limit theorems: law of large numbers, central limit theorem. Markov chains: transition probabilities, stationary distributions, reversibility, convergence.

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Lecture 33: Joseph Blitzstein:

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Lecture Details

Joe Blitzstein teaches the popular statistics class Stat 110, which provides a comprehensive introduction to probability as a medium to understand statistics, science, risk, and randomness. It has grown to over 300 students per year at Harvard and over 200,000 subscribers on iTunes U. His main research interests are in statistical inference for complex networks, with applications to social science and public health. Personally, he enjoys playing chess and is ranked in the Expert range by the US Chess Federation (the 98th percentile of all tournament players), and is the faculty adviser for the Harvard Chess Club.