strong law of large numbers

Summary

Roughly, the laws of large numbers state that the average of a large number of draws of a random variable approaches the expectation. The strong law states that the probability that the average of the sequence fails to converge to the expectation is zero. This is a strictly stronger statement than the weak law, but requires stronger assumptions.

Context

This concept has the prerequisites:

independent random variables (The strong law is a statement about independent random variables.)
expectation and variance (The strong law is about convergence to an expectation.)
weak law of large numbers

Core resources (we're sorry, we haven't finished tracking down resources for this concept yet)

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

-Free-

→ Mathematical Monk: Probability Primer (2011)

Online videos on probability theory.

Location: Lecture 5.5, "Law of large numbers and Central Limit Theorem"

[external website]

-Paid-

→ A First Course in Probability

An introductory probability textbook.

Location: Section 8.4, "The strong law of large numbers," pages 443-445