Statistics
maTH library also supports some distributions from statistics. Here's a list of them all:
Binomial(n, p)
Number of successes in a sequence of n independent experiments, all with constant probability of p.
Poisson(lambda)
Expresses the probability of a given number of events occurring in a fixed interval of time or space if these events occur with a known constant mean rate (lambda) and independently of the time since the last event.
Geometric(p)
Describes when the first success in an infinite sequence of independent and identically distributed Bernoulli trials occurs.
Pascal(r, p)
Also known as negative binomial distribution, expresses the number of failures in a sequence of independent and identically distributed Bernoulli trials before a specified number of successes (r) occurs.
Hypergeometric(K, N, n)
Describes the probability of k successes in n draws, without replacement, from a finite population of size N that contains exactly K objects with that feature, wherein each draw is either a success or a failure.
Exponential(lambda)
The probability distribution of the distance between events in a Poisson point process, i.e., a process in which events occur continuously and independently at a constant average rate (lambda)
Uniform(a, b)
Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds [a, b].
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