Law of large numbers

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.

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