## Poisson Distribution Explained

Poisson Distribution outputs the probability of a sequence of events happening in a fixed time interval.

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# Category: Probability

## Poisson Distribution Explained

Poisson Distribution outputs the probability of a sequence of events happening in a fixed time interval.

Probability, Probability Distributions
## Uniform Probability Distribution

Probability, Probability Distributions
## Negative Binomial Distribution

Probability, Probability Distributions
## Binomial Probability Distribution

Probability, Probability Distributions
## Probability Mass Function

Probability, Probability Distributions, Statistics
## Expected Value

Probability, Probability Distributions, Statistics

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In a Uniform Distribution Probability Density Function (PDF) is same for all the possible X values. Sometimes this is called a Rectangular Distribution. There are two (2) parameters in this distribution, a minimum (A) and a maximum (B)

In the Negative Binomial Distribution, we are interested in the number of Failures in n number of trials. This is why the prefix “Negative” is there. When we are interested only in finding number of trials that is required for a single success, we called it a Geometric Distribution.

Binomial Distribution is used to find probabilities related to Dichotomous Population. It can be applied to a Binomial Experiment where it can result in only two outcomes. Success or Failure. In Binomial Experiments, we are interested in the number of Successes.

Probability Mass Function (PMF) of X says how the total probability of 1 is distributed (allocated to) among the various possible X values.

Expected Value is the average value we get for a certain Random Variable when we repeat an experiment a large number of times. It is the theoretical mean of a Random Variable. Expected Value is based on population data. Therefore it is a parameter.