Population, Sample and Central Limit Theorem (CLT)

Population and Sample

‘Population’ term here means all people around in the world.

  1. There is high chance that people might enter the wrong height value.
  2. Even if it correctly entered their height value, there are 7.7 billions!! total number of people around in the world. So, the size of the file will increase so significantly and most of the system can’t afford to load that large amount of data.

Central Limit Theorem (CLT)

Before, we understand it definition, let understand its concept. (Because once you understand the concept, then you can able to define this theorem)

Perform sampling ’N’ times and each sample has a sample size = ‘Ns’
Mean and Variance are in Equally Approximation (NOT ACCURATE)
Here S_Bar means Average of Sample data

Observation I (Number of Samples = 100, Each sample size=30)

Note: Let observe why we divide by sample size

Observation II (Number of Samples = 100, Each sample size=10,000)

Observation III (Number of Samples = 100, Each sample size=20,000)

--

--

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store