&gt;&quot;In order to estimate what is the true mean of our variants statisticians rely on the Central Limit Theorem (CLT) 6 which states that the sampling distribution of any statistic will be normal or nearly normal, if the sample size is large enough.&quot;<p>Wow, no. This is a very dangerous misconception. First sentence of the wikipedia page gives a much better definition:<p>&quot;In probability theory, the central limit theorem (CLT) states that, given certain conditions, the arithmetic mean of a sufficiently large number of iterates of independent random variables, each with a well-defined expected value and well-defined variance, will be approximately normally distributed, regardless of the underlying distribution.&quot;<p><a href="https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Central_limit_theorem" rel="nofollow">https:&#x2F;&#x2F;en.wikipedia.org&#x2F;wiki&#x2F;Central_limit_theorem</a>