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# Binomial Distribution

Fit, evaluate, and generate random samples from binomial distribution

Statistics and Machine Learning Toolbox™ offers several ways to work with the binomial distribution.

• Create a probability distribution object `BinomialDistribution` by fitting a probability distribution to sample data or by specifying parameter values. Then, use object functions to evaluate the distribution, generate random numbers, and so on.

• Work with the binomial distribution interactively by using the Distribution Fitter app. You can export an object from the app and use the object functions.

• Use distribution-specific functions with specified distribution parameters. The distribution-specific functions can accept parameters of multiple binomial distributions.

• Use generic distribution functions (`cdf`, `icdf`, `pdf`, `random`) with a specified distribution name (`'Binomial'`) and parameters.

To learn about the binomial distribution, see Binomial Distribution.

## Objects

 `BinomialDistribution` Binomial probability distribution object

## Apps

 Distribution Fitter Fit probability distributions to data Probability Distribution Function Interactive density and distribution plots

## Functions

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#### Create `BinomialDistribution` Object

 `makedist` Create probability distribution object `fitdist` Fit probability distribution object to data

#### Work with `BinomialDistribution` Object

 `cdf` Cumulative distribution function `icdf` Inverse cumulative distribution function `iqr` Interquartile range `mean` Mean of probability distribution `median` Median of probability distribution `negloglik` Negative loglikelihood of probability distribution `paramci` Confidence intervals for probability distribution parameters `pdf` Probability density function `proflik` Profile likelihood function for probability distribution `random` Random numbers `std` Standard deviation of probability distribution `truncate` Truncate probability distribution object `var` Variance of probability distribution
 `binocdf` Binomial cumulative distribution function `binopdf` Binomial probability density function `binoinv` Binomial inverse cumulative distribution function `binostat` Binomial mean and variance `binofit` Binomial parameter estimates `binornd` Random numbers from binomial distribution
 `mle` Maximum likelihood estimates
 `distributionFitter` Open Distribution Fitter app `qqplot` Quantile-quantile plot `randtool` Interactive random number generation

## Topics

Bernoulli Distribution

The Bernoulli distribution is a discrete probability distribution with only two possible values for the random variable.

Binomial Distribution

The binomial distribution models the total number of successes in repeated trials from an infinite population under certain conditions.

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