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Binomial cumulative distribution function

computes a binomial cumulative distribution function at each of the values in
`y`

= binocdf(`x`

,`n`

,`p`

)`x`

using the corresponding number of trials in `n`

and the probability of success for each trial in `p`

.

`x`

, `n`

, and `p`

can be
vectors, matrices, or multidimensional arrays of the same size. Alternatively, one or more
arguments can be scalars. The `binocdf`

function expands scalar inputs to
constant arrays with the same dimensions as the other inputs.

`binocdf`

is a function specific to binomial distribution. Statistics and Machine Learning Toolbox™ also offers the generic function`cdf`

, which supports various probability distributions. To use`cdf`

, specify the probability distribution name and its parameters. Alternatively, create a`BinomialDistribution`

probability distribution object and pass the object as an input argument. Note that the distribution-specific function`binocdf`

is faster than the generic function`cdf`

.Use the

**Probability Distribution Function**app to create an interactive plot of the cumulative distribution function (cdf) or probability density function (pdf) for a probability distribution.