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.
-Paid-
→ A First Course in Probability
An introductory probability textbook.
Location:
Section 8.4, "The strong law of large numbers," pages 443-445
See also
-No Additional Notes-