General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

Seedable random number generator supporting many common distributions.

Learning Statistics is one of the most Important step to get into the World of Data Science and Machine Learning. Statistics helps us to know data in a much better way and explains the behavior of the data based upon certain factors. It has many Elements which help us to understand the data better that includes Probability, Distributions, Descri…

🚀 A library designed to facilitate work with probability, statistics and stochastic calculus

ROS package for NDT-PSO, a 2D Laser scan matching algorithm for SLAM

PHP implementation of statistical probability distributions: normal distribution, beta distribution, gamma distribution and more.

Gauss Naive Bayes in Python From Scratch.

An algorithm based on Java implementation, can automatically check the set of outliers in a set of data, eliminate these outliers, and finally get normal data.基于java实现的能够自动检查出一组数据中的异常值的集合，剔除这些异常集，得到正常数据。

10 Days of Statistics Challenges at HackerRank

Free WordPress Plugin: The probability calculator can find two events' probability and the normal distribution probability. Learn more about probability's laws and calculations. www.calculator.io/probability-calculator/

LambertW R package: Lambert W x F distributions and Gaussianization for skewed & heavy-tailed data

Package provides the javascript implementation of various statistics and distribution

A MATLAB project which applies the central limit theorem on PDFs and CDFs of different probability distributions.

Experiment with Benford's Law to find data anomalies in number lists and images (Windows, macOS, Linux, .NET 8.0, x64, Arm64, Apple Silicon)

Compute mean and variance of the univariate truncated normal distribution (works far from the peak).

Fast Gaussian distributed pseudorandom number generation in Java via the Ziggurat algorithm

This Jupyter notebook demonstrates how to properly plot uncertainty (confidence) ellipses for 2D normally distributed data.

[R] Statistical analysis of financial data conducted in R

gips - Gaussian model Invariant by Permutation Symmetry

C++ and Julia Normal distribution generated with uniform distribution