independent events

(1.4 hours to learn)


Intuitively, two events are independent if the first event happening doesn't influence whether the second is likely to occur. Mathematically, some set of events are independent if the joint probability of some subset of the events decomposes into a product of the probabilities of the individual events. In statistics and AI, a probabilistic model often must make independence assumptions in order for things to be efficiently computable.


This concept has the prerequisites:

Core resources (read/watch one of the following)


Mathematical Monk: Probability Primer (2011)
Online videos on probability theory.
Other notes:
  • This uses the measure theoretic notion of probability, but should still be accessible without that background. Refer to Lecture 1.S for unfamiliar terms.


Supplemental resources (the following are optional, but you may find them useful)


BerkeleyX: Introduction to Statistics: Probability
An online course on basic probability.
Location: Lecture 2.1, "Independence"
Sets, Counting, and Probability
Online lectures on basic probability theory.
Location: Lecture sequence "Conditional probability"
Khan Academy: Probability and Statistics

See also