Binomial Distribution vs. Poisson Distribution: Know the Difference
By Shumaila Saeed || Published on January 31, 2024
Binomial Distribution is used for a fixed number of trials with two outcomes, while Poisson Distribution deals with the probability of events occurring in a fixed interval of time or space.
Key Differences
Binomial Distribution applies to scenarios with a fixed number of trials, each having two possible outcomes (success or failure). Poisson Distribution is used for calculating the likelihood of a given number of events happening in a fixed period of time or space.
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Jan 31, 2024
In Binomial Distribution, the outcomes of the trials are discrete and independent, with a fixed probability of success. Poisson Distribution assumes that events occur independently and the probability of occurrence is the same across any two intervals of equal length.
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Jan 31, 2024
Binomial Distribution is characterized by two parameters: the number of trials (n) and the probability of success (p) in each trial. Poisson Distribution is defined by a single parameter, λ (lambda), which is the average number of occurrences in a given interval.
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Jan 31, 2024
Binomial Distribution is suitable for situations like flipping a coin a certain number of times or quality control in manufacturing. Poisson Distribution is apt for scenarios like the number of cars passing a point in an hour or the number of typing errors on a page.
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Jan 31, 2024
The probability in Binomial Distribution is calculated using the binomial formula, involving combinations. In Poisson Distribution, the probability of a given number of events is calculated using the Poisson formula, involving e (the base of the natural logarithm).
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Jan 31, 2024
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Comparison Chart
Definition
Probability of a fixed number of successes in a set number of trials
Probability of a number of events in a fixed interval
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Outcomes
Two possible outcomes (success/failure)
Number of occurrences in an interval
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Parameters
Number of trials (n), probability of success (p)
Average rate of occurrence (λ)
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Probability Formula
Binomial formula involving combinations
Poisson formula involving e (Euler's number)
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Binomial Distribution and Poisson Distribution Definitions
Binomial Distribution
It represents the probabilities of outcomes with only two possibilities in each trial.
Binomial distribution is used to determine the likelihood of 8 defective items in a batch of 50.
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Poisson Distribution
Poisson distribution applies to scenarios where events are independent and occur at a constant rate.
The Poisson distribution estimates the number of emails a person might receive in a day.
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Binomial Distribution
A discrete probability distribution for a fixed number of trials with a constant probability of success.
The binomial distribution helps calculate the probability of receiving 3 calls out of 10 in a call center.
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Poisson Distribution
It measures the likelihood of a certain number of events happening within a set period or area.
Using Poisson distribution, one can estimate the number of stars visible in a certain sky section.
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Binomial Distribution
Binomial distribution quantifies the outcomes of binary scenarios over several trials.
When flipping a coin 30 times, the binomial distribution can be used to find the probability of 20 tails.
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Poisson Distribution
A mathematical representation for counting the number of events in continuous intervals.
In a bookstore, Poisson distribution can help predict the number of customers arriving per hour.
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Binomial Distribution
A probability distribution of the number of successes in a fixed number of independent trials.
In a series of 10 coin flips, the binomial distribution can calculate the probability of getting exactly 6 heads.
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Poisson Distribution
A distribution that expresses the probability of a given number of events occurring in a fixed interval.
Poisson distribution can predict the probability of 5 cars passing a bridge in 10 minutes.
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Binomial Distribution
A statistical distribution based on the number of successes and failures in experiments.
In a test of 20 questions (true or false), binomial distribution predicts the chances of scoring 15 correct answers.
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Poisson Distribution
A statistical distribution describing the occurrence of rare events over a fixed time or space.
Poisson distribution is used to assess the chance of two earthquakes occurring in a week.
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Repeatedly Asked Queries
What are Bernoulli trials in the context of a Binomial Distribution?
Bernoulli trials are experiments with only two possible outcomes: success and failure.
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Jan 31, 2024
What are some real-life examples of situations modeled by a Binomial Distribution?
Examples include coin tosses, success/failure in product manufacturing, and pass/fail rates in exams.
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Jan 31, 2024
Can the number of trials (n) be any positive integer in a Binomial Distribution?
Yes, n can be any positive integer, representing the fixed number of trials.
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What is a Binomial Distribution?
It is a probability distribution that models the number of successes in a fixed number of independent Bernoulli trials.
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Jan 31, 2024
What are the parameters of a Binomial Distribution?
The parameters are the number of trials (n) and the probability of success (p) on each trial.
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What is the formula for calculating the probability in a Binomial Distribution?
P(X = k) = (n choose k) * p^k * (1-p)^(n-k)
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What is the mean and variance of a Binomial Distribution?
Mean (μ) = n * p, Variance (σ²) = n * p * (1-p)
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Jan 31, 2024
What is the difference between a Binomial and Bernoulli Distribution?
A Bernoulli Distribution models a single trial, while a Binomial Distribution models multiple trials with the same probability of success.
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Jan 31, 2024
What is a Poisson Distribution?
It is a probability distribution that models the number of events occurring in a fixed interval of time or space.
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Is the outcome in a Binomial Distribution mutually exclusive?
Yes, outcomes in a Binomial Distribution are mutually exclusive, meaning one success does not affect the probability of another.
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Jan 31, 2024
What is the probability mass function (PMF) for a Poisson Distribution?
P(X = k) = (e^(-λ) * λ^k) / k!
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When is the Poisson Distribution particularly useful?
It is useful when events occur randomly and independently at a constant average rate.
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What happens to the shape of a Binomial Distribution as n increases?
As n increases, the Binomial Distribution approaches a normal distribution.
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Can the Poisson Distribution be used for rare events and large values of λ?
Yes, it is suitable for modeling rare events when λ is relatively small.
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Jan 31, 2024
Are outcomes in a Poisson Distribution mutually exclusive?
Yes, outcomes are mutually exclusive, meaning events cannot occur simultaneously within the same interval.
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Jan 31, 2024
What are the parameters of a Poisson Distribution?
The parameter is the average rate (λ) at which events occur in the given interval.
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Jan 31, 2024
What is the difference between a Poisson and Binomial Distribution?
A Poisson Distribution models events in continuous time or space, while a Binomial Distribution models discrete trials.
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Jan 31, 2024
What is the relationship between λ and the mean in a Poisson Distribution?
The mean (μ) of a Poisson Distribution is equal to λ.
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What is the variance of a Poisson Distribution?
Variance (σ²) = λ, which is also equal to the mean.
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Jan 31, 2024
Can the Poisson Distribution model events that occur continuously, like arrivals at a bus stop?
Yes, it can model continuous events when the interval is divided into smaller time intervals.
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Jan 31, 2024
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About Author
Written by
Shumaila SaeedShumaila Saeed, an expert content creator with 6 years of experience, specializes in distilling complex topics into easily digestible comparisons, shining a light on the nuances that both inform and educate readers with clarity and accuracy.
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