This law basically predicts everything
“Law of Large Numbers/Law of Average”
It says “Over a large number of trials, outcomes tend to move closer to the expected probability.”
This also explains why you need to work with large dataset
Let’s dive in🔥
The Law of Large Numbers (LLN) says:
As the number of trials increases, the average result of random events gets closer to the true expected value.
In simple terms:
The more you repeat something random, the more predictable it becomes.
Example: flipping a coin:
The probability of Heads = 50%
But if you flip it just 5 times, you might get 4 heads and 1 tail (80% heads).
Flip it 1000 times → the proportion of heads will settle close to 50%.
That’s LLN in action.
This also explains why few trials might not get you results.
But consistently increasing the number of trials will give you what you want.
Example: when applying for jobs, the more the applications you submit the more likely you’re going to get a job.
The more time you dedicate to learning the more likely it is you’re going to get good
This is one of the best law I have came across🤯
This is also why if you stay in one business for a very long period of time you will eventually end up making profits.
“This is mind blowing”
What LLN is NOT:
It doesn’t mean results “balance out” in the short term.
That’s the GAMBLERS FALLACY (thinking a tails is due after 5 heads).
Each coin flip is still independent with 50/50 chance.
The Law of Large Numbers reminds us:
Don’t trust small samples.
Don’t confuse short-term randomness with long-term patterns.
In the long run, averages tell the truth.
That’s why statisticians love large datasets 📊
This right here! Great post