Statistics – Weak Law of Large Numbers

Prabhu TL
1 Min Read
Disclosure: This website may contain affiliate links, which means I may earn a commission if you click on the link and make a purchase. I only recommend products or services that I personally use and believe will add value to my readers. Your support is appreciated!

The weak law of large numbers is a result in probability theory also known as Bernoulli’s theorem. Let P be a sequence of independent and identically distributed random variables, each having a mean and standard deviation.

Formula

0=limn→∞P{|X−μ|>1n} =P{limn→∞{|X−μ|>1n}} =P{X≠μ}0=limn→∞P{|X−μ|>1n} =P{limn→∞{|X−μ|>1n}} =P{X≠μ}

Where −

·        nn = Number of samples

·        XX = Sample value

·        μμ = Sample mean

Example

Problem Statement:

A six sided die is rolled large number of times. Figure the sample mean of their values.

Solution:

Sample Mean Calculation

Sample Mean=1+2+3+4+5+66 =216,=3.5

Share This Article
Prabhu TL is a SenseCentral contributor covering digital products, entrepreneurship, and scalable online business systems. He focuses on turning ideas into repeatable processes—validation, positioning, marketing, and execution. His writing is known for simple frameworks, clear checklists, and real-world examples. When he’s not writing, he’s usually building new digital assets and experimenting with growth channels.
Leave a review