Though this article tackles **binomial distribution**, a type of discrete probability distribution, it is rather focused on practical questions how to use matplotlib to construct such distributions.

Numpy offers four parameters that effect graphical appearance:

parameter |
meaning |
usage |

p |
probability |
essential, to construct a probability distribution |

n |
sample size |
essential, to construct a probability distribution |

loc |
origin |
optional, the origin of the probability distribution default = 0 |

size |
vector length |
optional, size of the one dimensional array of random variables default=0 => no array but a single random variable is returned |

[Error: Macro 'mathplot' error: mathplot() got an unexpected keyword argument 'title']

The probability mass function can be written:

[Error: Macro 'me' doesn't exist]

The cumulative probability function can be described by the equation:

[Error: Macro 'me' doesn't exist]