Probability Mass Function of Poisson Distribution
Probability Mass Function for Poisson Distribution is given by:
[Tex]\bold{\text{PMF} = \frac{\lambda^k e^{-\lambda}}{k !}}[/Tex]
where,
- λ is Parameter which is also equal to Mean and Variance
- k is Number of times an event occurs
- e is Euler’s Number (≈2.718)
Poisson Distribution | Definition, Formula, Table and Examples
Poisson Distribution is one of the types of discrete probability distributions like binomial distribution in probability. It expresses the probability of a given number of events occurring in a fixed interval of time.
Poisson distribution is a type of discrete probability distribution that determines the likelihood of an event occurring a specific number of times (k) within a designated time or space interval. This distribution is characterized by a single parameter, λ (lambda), representing the average number of occurrences of the event.
In this article, we will discuss the Poisson Distribution including its definition, Poisson Distribution formula, Poisson Distribution examples, and properties of Poisson Distribution in detail.
Table of Content
- What is Poisson Distribution?
- Poisson Distribution Definition
- Poisson Distribution Formula
- Poisson Distribution Table
- Poisson Distribution Characteristics
- Poisson Distribution Graph
- Poisson Distribution Mean and Variance
- Poisson Distribution Mean
- Poisson Distribution Variance
- Standard Deviation of Poisson Distribution
- Probability Mass Function of Poisson Distribution
- Difference between Binomial and Poisson Distribution
- Poisson Distribution Examples
- Poisson Distribution Practice Problems