In this video, we’ll talk about the real-world application of one of the most widely used theorems in data science: The Central Limit Theorem. The Central Limit Theorem is the core of ‘hypothesis testing’- an approach in statistics that lets you use data to evaluate your ideas. In fact, this theorem can be applied to a variety of real-life problems. We will illustrate it with an interesting example of a business in the fish market area.
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The Central Limit Theorem is a theorem in probability theory, whose first version was proposed by the French mathematician Abraham de Moivre in 1733. Moivre published an article where he used a normal distribution to approximate the distribution of the number of heads resulting from many tosses of a fair coin. The finding was nearly forgotten until the French mathematician Pierre-Simon Laplace expanded it in his monumental work in the 19th century. Over the years, numerous versions of it have been discovered and proven by other mathematicians. Fascinating, right? Watch the video to learn more!
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