### numbers.random

#### numbers.random.bates(n, b, a)

Generates a random number according to a Bates distribution inside the interval [a,b]. Both arguments are optional.

Parameters n : Int Number of times to sum. b : Number, optional Right endpoint of interval. Default value is 1. a : Number, optional Left endpoint of the interal. Default value is 0. num : Number Random number according to a Bates distribution on [a,b]. This function does not raise any errors.

#### numbers.random.boxMullerTransform(mu, sigma)

Generates a pair of indepedent pseudo-random numbers from a normal distribution with mean mu and standard deviation sigma. Both arguments are optional.

Parameters mu : Number, optional Mean. Default value is 1. sigma : Number, optional Standard deviation. Default value is 0. arr : Array A pair of random numbers according to a normal distribution with mean mu, standard deviation sigma. This function does not raise any errors.

#### numbers.random.distribution.bates(n, b, a)

Creates an array of n random numbers according to an Bates distribution inside the interval [a,b]. a and b are optional arguments.

Parameters n : Int Amount of random numbers to generate. b : Number, optional Right endpoint of interval. Default value is n. a : Number, optional Left endpoint of interval. Default value is 0. arr : Array An array of n random numbers from a Bates distribution on [a,b]. This function does not raise any errors.

#### numbers.random.distribution.boxMuller(n, mu, sigma, rc)

Creates an array of n random numbers according to the Box-Muller transform with a mean mu and standard deviation sigma. ru determines if the returned value will be in polar coordinates. mu, sigma and rc are optional arguments.

Parameters n : Int Amount of random numbers to generate. mu : Number, optional Mean. Default value is 1. sigma : Number, optional Standard deviation. Default value is 0. rc : Boolean, optional Determine if returned values should be in polar coordinates (true) or not (false). Default value is false. arr : Array An array of n random numbers from a normal distribution with mean mu, standard deviation sigma. This function does not raise any errors.

#### numbers.random.distribution.irwinHall(n, m, sub)

Creates an array of n random numbers according to an Irwin-Hall distribution with a maximum sum value of m and a subtraction value of sub. mu and sub are optional arguments.

Parameters n : Int Amount of random numbers to generate. m : Number, optional Maximum sum value. Default value is n. sub : Number, optional Number to subtract. Default value is 0. arr : Array An array of n random numbers from a normal distribution with mean mu, standard deviation sigma. This function does not raise any errors.

#### numbers.random.distribution.irwinHallNormal(n)

Creates an array of n random numbers (approximately) according to a normal distribution with bounds (-6, 6).

Parameters n : Int Amount of random numbers to generate. arr : Array An array of n random numbers from a normal distribution with bounds (-6,6). This function does not raise any errors.

#### numbers.random.distribution.logNormal(n, mu, sigma)

Creates an array of n random numbers according to a log-normal distribution with a mean mu and standard deviation sigma. mu and sigma are optional arguments.

Parameters n : Int Amount of random numbers to generate. mu : Number, optional Mean. Default value is 1. sigma : Number, optional Standard deviation. Default value is 0. arr : Array An array of n random numbers from a log-normal distribution with mean mu, standard deviation sigma. This function does not raise any errors.

#### numbers.random.distribution.normal(n, mu, sigma)

Creates an array of n random numbers according to a normal distribution with a mean mu and standard deviation sigma. mu and sigma are optional arguments.

Parameters n : Int Amount of random numbers to generate. mu : Number, optional Mean. Default value is 0. sigma : Number, optional Standard deviation. Default value is 1. arr : Array An array of n random numbers from a normal distribution with mean mu, standard deviation sigma. This function does not raise any errors.

#### numbers.random.irwinHall(n, sub)

Generates a random number according to an Irwin-Hall distribution, given a maximum sum, n, and a number to subtract, sub.

Parameters n : Number Maximum sum. sub : Number Number to subtract. num : Number Random number according to an Irwin-Hall distribution. This function does not raise any errors.

#### numbers.random.sample(a, b, n)

Generates an array of n uniformly distributed random numbers inside the interval [a,b].

Parameters a : Int Left endpoint of interval. b : Int Right endpoint of interval. n : Int Amount of random numbers to generate. arr : Array An array of n random numbers inside [a,b]. This function does not raise any errors.