Statistics 110: Introduction to Probability by Joseph Blitzstein.
Description:
Statistics 110 (Introduction to Probability), taught at Harvard University by Joe Blitzstein in Fall 2011. Lecture videos, homework, review material, practice exams, and a large collection of practice problems with detailed solutions are provided. 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, philosophy, engineering, economics, finance, and everyday life. Topics include the following. Basics: sample spaces and events, conditional probability, Bayes’ Theorem. Random variables and their distributions: cumulative distribution functions, 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.
Like Michael Heise, I haven’t watched the lectures but I would appreciate hearing comments from anyone who does.
Particularly in an election year where people are going to be using (mostly abusing) statistics to influence your vote in city, county (parish in Louisiana), state and federal elections.
First seen at Statistics via iTunes by Michael Heise.