- The standard deviation of the population distribution is tied with the standard deviation of the sampling distribution.
- With the standard deviation of the sampling distribution and the sample size, we are able to calculate the standard deviation of the population distribution.
- The standard deviation of the sampling distribution is called the standard error.
- The mean of the sampling distribution will cluster around the population mean.
- If we collect a large number of different samples mean, the distribution of those samples mean should take the shape of a normal distribution no matter what the population distribution is.
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@MikeTamir: “The Theorem Every Data Scientist Should Know (Part 2) #MachineLearning #DataScience”
Last week, I wrote a post about the Central Limit Theorem. In that post, I explained through examples what the theorem is and why it’s so important when working with data. If you haven’t read it yet, go do it now. To keep the post short and focused, I didn’t go into many details. The goal of that post was to communicate the general concept of the theorem. In the days following it’s publication, I received many messages. People wanted me to go into more details.
The Theorem Every Data Scientist Should Know (Part 2) · Jean-Nicholas Hould