From the course: Probability Foundations for Data Science

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Poisson distribution

Poisson distribution

From the course: Probability Foundations for Data Science

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Poisson distribution

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- [Instructor] In this video, I will wrap up discrete distributions by showing you how to use the Poisson distribution to gather probability over periods of time. The Poisson distribution works with discrete random variables to model the number of events that occur over a fixed interval of time or space. These events happen with a known constant average rate, and they're independent from the time since the last event. The Poisson distribution is represented by two variables. The first variable is Lambda, which is the average number of events that occur in a given interval of time or space. Note, the Lambda symbol is the standard one to use with this distribution instead of X like many other distributions. The second variable is K, which represents the number of occurrences of the event. The Poisson on distribution is represented by the following probability mass function, where you have the probability of X equaling K equal to Lambda to the K multiplied by E to the negative lambda…

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