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  • Ankur Sawhney thinks this is interesting:

The central limit theorem states that if Z is the sum of n independent, identically distributed random variables with a finite, nonzero standard deviation, then the probability distribution of Z approaches the normal distribution as n increases.

From

Cover of Essential Statistics, Regression, and Econometrics

Note

This basically states that ANY collection of events DESIGNED TO READ/WRITE/DO A COMMON THING has a high probability of coming out with an average value ( that represents the collection ) of collection as the no. of events making the collection increase.
The opposite being that ANY collection of events DESIGNED TO READ/WRITE/DO A COMMON THING has a very low probability of coming out with a very high or very low value ( that represents the collection ) of collection as the no. of events making the collection increase.

IN OTHER WORDS, if you together do / write / read a job, then, there's a high probability that you will together do an average job as long as you are huge in no.

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