I am trying to clarify these two concepts - and understand the differences between the Central Limit Theorem (https://en.wikipedia.org/wiki/Central_limit_theorem) and the Weak Law of Large Numbers (https://en.wikipedia.org/wiki/Law_of_large_numbers).
As an example, suppose I have a coin and I don't know the true probability of Heads or Tails - I start to flip the coin again and again:
- The Law of Large Numbers states that if I flip this coin enough times, I will get an estimate of the true probability of getting a Heads
- The Central Limit Theorem states that as I flip the coin again and again, the distribution for the probability of getting a Heads will follow a Standard Normal Distribution
Is my understanding of this correct?