In probability theory, the law of large numbers (LLN) is a theorem that describes the result of performing the same experiment a large number of times. According to the law, the average of the results obtained from a large number of trials should be close to the expected value, and will tend to become closer as more trials are performed.

## Strong Law

The strong law of large numbers states that the sample average converges almost surely to the expected value.

## Weak Law

The weak law of large numbers (also called Khinchin’s law) states that the sample average converges in probability towards the expected value.