18.600: Probability and Random Variables

Intro to probability with some mathematical rigor. Helped me learn how to find clever mathematical transformations / proofs, thanks to kind TAs :)

From the course catalog:

  • Part 1: Probability spaces, random variables, distribution functions, counting.
  • Part 2: Binomial, geometric, negative binomial, Poisson distributions. Uniform, exponential, normal, gamma and beta distributions. Conditional probability, Bayes theorem, joint distributions.
  • Part 3: Markov/Chebyshev/Chernoff inequalities, weak/strong laws of large numbers, central limit theorem, martingales, markov chains, entropy.

Cheatsheets

Last updated: 31 December 2024

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