1.
Introduction
2.
Derivation of Poisson Distribution
3.
Calculation of Expected Value in Poisson Distribution
4.
Calculation of Variance in Poisson Distribution
5.
FAQs
6.
Key Takeaways
Last Updated: Mar 27, 2024

# Poisson Distribution

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## Introduction

A Poisson distribution is a probability distribution used to calculate the probability of the number of times an independent event would occur in a specified period of time. A random variable is a variable whose total number of occurrences is unknown. A random variable follows the Poisson distribution.

To brush up on your knowledge of Mean, Variance and Standard Deviation, you can read the article Mean, Variance and Standard Deviation on Coding Ninjas Studio.

## FAQs

1. What is the probability of x success in n trials of an independent event with probability success p?

The probability is given by

P(x) = nCx px  (1-p)x

2. What is the expected value for an independent event for n trials with probability success p?

The expected value is equal to the product of the number of trials and the success rate. Thus Expected value = n x p.

3. What is the formula of kCn?

The formula is given by kCn = factorial(k)/(factorial(k-n)*factorial(n))

4. What is the Poisson distribution formula?

The Poisson distribution formula is given by

5. What are the application of the Poisson Distribution?

The Poisson Distribution is used to calculate the probability of the number of calls at a call centre, number of website visitors per month, number of arrivals at a restaurant etc.

## Key Takeaways

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