Poisson Distribution

Understand the Poisson distribution with simple explanations, meaning, conditions, formula, mean, variance, and real-life examples involving rare events.

1. Meaning of a Poisson Distribution

A Poisson distribution is used to model the probability of a certain number of events happening in a fixed interval of time or space when the events occur rarely and independently.

It helps when events happen randomly but with a known average rate.

1.1. Examples

  • Number of phone calls received by a help desk in 1 minute.
  • Number of printing errors per page of a book.
  • Number of cars passing a point in 30 seconds.

2. When Poisson Distribution is Used

A Poisson distribution is suitable when the following conditions are met:

2.1. Events Are Rare

The events occur infrequently compared to the time or space interval.

2.2. Events Occur Independently

One event happening does not affect the chance of another event happening.

2.3. Constant Average Rate

The events happen with a fixed average rate, denoted by \( \lambda \) (lambda).

2.4. Events Occur One at a Time

Two or more events do not occur at exactly the same moment.

3. Poisson Probability Formula

If X is the number of events in a fixed interval, then the probability that exactly k events occur is:

\( P(X = k) = \dfrac{\lambda^k e^{-\lambda}}{k!} \)

Here:

  • \( k \) = number of events
  • \( \lambda \) = average rate of events
  • \( e \approx 2.718 \)

3.1. Example

If a call centre receives an average of 3 calls per minute, what is the probability of receiving exactly 2 calls in a minute?

Here \( \lambda = 3 \) and \( k = 2 \).

\( P(X = 2) = \dfrac{3^2 e^{-3}}{2!} = \dfrac{9e^{-3}}{2} \)

4. Mean and Variance

A Poisson distribution has equal mean and variance, both given by:

\( \mu = \lambda, \quad \sigma^2 = \lambda \)

4.1. Example

If the average number of misprints per page is 0.8, then:

  • Mean = 0.8
  • Variance = 0.8

5. More Examples

Situations where Poisson distribution applies:

5.1. Accidents or Failures

Number of accidents happening in a day or number of machine breakdowns in a week.

5.2. Requests or Arrivals

Number of customers arriving at a shop in 10 minutes.

5.3. Counts Over Space

Number of bacteria in a square centimetre of a slide.