Our group, along with a few students, has been reading statistics handbook and refreshing our understanding of the basic statistics. I was given to cover a chapter about the central limit theorem, which reminded me that I had already given a similar presentation while being PhD student myself. While diving into the topic, I have noticed a couple things, which are usually glanced over in a typical statistics handbook. Let me share them with you.

In the previous post we have taken a look at a distribution whose mean and variance are undefined. We know that the central limit theorem holds only if mean and variance of the sample distribution are defined and finite. So what happens if we sum Cauchy random variates?

Our group, along with a few students, has been reading statistics handbook and refreshing our understanding of the basic statistics. I was given to cover a chapter about the central limit theorem, which reminded me that I had already given a similar presentation while being PhD student myself. While diving into the topic, I have noticed a couple things, which are usually glanced over in a typical statistics handbook. Let me share them with you.

In the previous post we have talked about a peculiar result in statistics - that an average of well-behaved random variates (those that come from distributions with finite mean and variance) is distributed according to the normal (Gaussian) distribution. But what happens if the variates are not well-behaved? Accompanying video briefly mentions Cauchy distribution, as a distribution describing random variates, which are not well-behaved. Let us take a look at it!

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We have already previously shared a video about the central limit theorem, but recently I have found another neat explanation by StatQuest. I would like to invite you to watch it.

Our group, along with a few students, has been reading statistics handbook and refreshing our understanding of the basic statistics. I was given to cover a chapter about the central limit theorem, which reminded me that I had already given a similar presentation while being PhD student myself. While diving into the topic, I have noticed a couple things, which are usually glanced over in a typical statistics handbook. Let me share them with you.

In the previous post we have started simple - with the law of large numbers. In this post, let us consider a natural extension of this result - the central limit theorem.