binomial distribution
Consider an experiment with two possible outcomes (success and failure), which happen randomly. Let be the probability of success. If the experiment is repeated times, the probability of having exactly successes is
The distribution function determined by the probability function is called a Bernoulli distribution or binomial distribution.
Here are some plots for with and , .
The corresponding distribution function is
where . Notice that if we calculate we get the binomial expansion for , and this is the reason for the distribution being called binomial.
We will use the moment generating function to calculate the mean and variance for the distribution. The mentioned function is
which simplifies to
Differentiating gives us
and therefore the mean is
Now for the variance we need the second derivative
so we get
and finally the variance (recall ):
For large values of , the binomial coefficients are hard to compute, however in this cases we can use either the Poisson distribution or the normal distribution to approximate the probabilities.
Title | binomial distribution |
Canonical name | BinomialDistribution |
Date of creation | 2013-03-22 13:03:01 |
Last modified on | 2013-03-22 13:03:01 |
Owner | Mathprof (13753) |
Last modified by | Mathprof (13753) |
Numerical id | 17 |
Author | Mathprof (13753) |
Entry type | Definition |
Classification | msc 60E05 |
Synonym | Bernoulli distribution |
Synonym | binomial random variable |
Synonym | binomial probability function |
Synonym | Bernoulli random variable |
Related topic | BinomialCoefficient |
Related topic | BinomialTheorem |
Related topic | BernoulliRandomVariable |