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Introduction to Probability

Harvard University via edX

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Overview

Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you tools needed to understand data, science, philosophy, engineering, economics, and finance. You will learn not only how to solve challenging technical problems, but also how you can apply those solutions in everyday life.

With examples ranging from medical testing to sports prediction, you will gain a strong foundation for the study of statistical inference, stochastic processes, randomized algorithms, and other subjects where probability is needed.

Syllabus

  • Unit 0: Introduction, Course Orientation, and FAQ
  • Unit 1: Probability, Counting, and Story Proofs
  • Unit 2: Conditional Probability and Bayes' Rule
  • Unit 3: Discrete Random Variables
  • Unit 4: Continuous Random Variables
  • Unit 5: Averages, Law of Large Numbers, and Central Limit Theorem
  • Unit 6: Joint Distributions and Conditional Expectation
  • Unit 7: Markov Chains

Taught by

Joseph Blitzstein

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