hypergeometric distribution
The hypergeometric distribution is a discrete probability distribution that describes the likelihood of obtaining a specific number of successes in a sample drawn without replacement from a finite population. Unlike the binomial distribution, where the probability of success remains constant, the hypergeometric distribution accounts for the changing probabilities as items are drawn. This distribution is particularly useful in scenarios such as card games or lottery systems, where the composition of the population affects the outcomes. Key parameters include the total population size, the number of successes in the population, the sample size, and the desired number of successes in the sample.
Understanding The Hypergeometric Distribution
The binomial distribution is a well-known distribution in and outside of data science. However, have you heard about its less popular cousin the hypergeometric distribution? Well if not, this post…
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Geometric Distribution Simply Explained
A simple description and uses of the Geometric distribution Continue reading on Towards Data Science
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Hypergeometric Distribution Explained With Python
With probability problems in a math class, the probabilities you need are either given to you or it is relatively easy to compute them in a straight-forward manner. But in reality, this is not the…
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Why Is The Log-uniform Distribution Useful For Hyperparameter Tuning?
Improve your grid search with this small change Continue reading on Towards Data Science
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Distributions
In the previous chapter we used Bayes’s Theorem to solve a cookie problem; then we solved it again using a Bayes table. In this chapter, at the risk of testing your patience, we will solve it one mor...
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