ts-gaussian 
A JavaScript model of the Normal
(or Gaussian) distribution.
API Docs: https://ts-gaussian.vercel.app
Creating a Distribution
import { Gaussian } from 'ts-gaussian';
const distribution = new Gaussian(0, 1);
const sample = distribution.ppf(Math.random());
Properties
mean: the mean (μ) of the distribution
variance: the variance (σ^2) of the distribution
standardDeviation: the standard deviation (σ) of the distribution
Probability Functions
pdf(x): the probability density function, which describes the probability
of a random variable taking on the value x
cdf(x): the cumulative distribution function, which describes the probability of a random variable falling in the interval (−∞, x]
ppf(x): the percent point function, the inverse of cdf
Combination Functions
mul(d): returns the product distribution of this and the given distribution; equivalent to scale(d) when d is a constant
div(d): returns the quotient distribution of this and the given distribution; equivalent to scale(1/d) when d is a constant
add(d): returns the sum of the means and variances of this distribution and the given distribution
sub(d): returns the difference of the means and variances of this distribution and the given distribution
scale(c): returns the result of scaling this distribution by the given constant
See Also
ts-trueskill: https://github.com/scttcper/ts-trueskill
Forked From
Source: https://github.com/errcw/gaussian
ES5 Fork: https://github.com/tomgp/gaussian