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…

Transcribing Speech with Multinomial Diffusion, training code and models.

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

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

10 Days of Statistics Challenges at HackerRank

PyPi package for modelling Probability distributions

Exercises solved for the Practical Statistics Module of Udacity's DAND: assignments and practice problems

Binomial and Beta-Binomial mixture models for counts data.

A Binomial Distribution Calculator with useful charts

Confidence intervals for binomial proportions.

This model can be used to find how many genes are involved in psychiatric disease. To verify the model we have taken the example of schizophrenia.

The binomial tree model is a commonly used approach for pricing derivatives, such as options. The basic idea behind the model is to create a tree of possible stock prices over time, based on a set of input parameters

An Jupyter notebook experimental discrete binomial distribution grapher

This repository contains the solutions to HackerRank's 10 Days of Statistics.

Option pricing models

Use random sampling to calculate probabililties of winning tennis matches based on constant and alternating probabilities of winning a (service) game.

A python package for easy dealing with Binomial and Gaussian distribution

Generation of random samples using R

VIBER - Variational Binomial Mixtures

The most common discrete and continuous distributions, showing how they find use in decision and estimation problems, and constructs computer algorithms for generating observations from the various distributions. and applications, and lastly the most important concept is covered is entropy