binomial

Binomial Distribution

A binomial distribution class, derived from a Udacity exercise template.

final class boring_math.probability_distributions.distributions.binomial.Binomial

Bases: DiscreteDist

Class for visualizing Binomial distributed data.

A Binomial distribution represents the number of events with probability p happening in n numbers of trials.

Attributes (some inherited):

• mean (float) representing the mean value of the distribution

• stdev (float) representing the standard deviation of the distribution

• data extracted from a data file (taken to be a population)

• p (float) representing the probability of an event occurring

• n (int) the total number of trials

__init__(p: float = 0.5, n: int = 20)

pdf(kf: float) → float

Binomial probability distribution function.

cdf(kf: float) → float

Binomial cumulative probability distribution function.

calculate_mean() → float

Calculate the mean from p and n

calculate_stdev() → float

Calculate the standard deviation using p and n

replace_stats_from_dataset(dset: DataSet) → tuple[float, int]

Function to calculate p and n from a data set.

Where the read in data set is taken as the population.

plot_bar_data() → None

Produce a bar-graph of the data using the matplotlib pyplot library.

plot_bar_pdf() → tuple[list[int], list[float]]

Function to plot the pdf of the binomial distribution.

Returns:

A tuple containing

• list[int]: x values used for the pdf plot

• list[float]: y values used for the pdf plot

__add__(other: Self) → Self

Add together two Binomial distributions with equal p.

__repr__() → str

Return repr(self).

__str__() → str

Return str(self).