Explore "Statistics" and "Probability Theory" Concepts and Their Implementations in "Python"
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Updated
Jul 12, 2024 - Jupyter Notebook
Explore "Statistics" and "Probability Theory" Concepts and Their Implementations in "Python"
📈📄👀A lookup repo for a variety of discrete and continuous distributions (incl. Beta, Binomial, Cauchy, Chi-squared, Geometric, Hypergeometric, Normal & Poisson)
The FactorGraph package provides the set of different functions to perform inference over the factor graph with continuous or discrete random variables using the belief propagation algorithm.
A courseware module that covers the fundamental concepts in probability theory and their implications in data science. Topics include probability, random variables, and Bayes' Theorem.
Stochastic sampling and statistical response analysis of systems with uncertain parameters
R package to help working with continuous random variables built for our Probabilities and Statistics course
Assignments and project related to the Statistics and Probability course, taught by Mohammad Karbasi.
Probability Methods for Informatics Engineering | UA 2018/2019
Implementation of the projects for the DSC 530: Probability and Statistics for Data Science course, of the MSc in Data Science programme of the University of Cyprus.
Python basics
Multi-core EBGstop algorithm implementation
🗑 Implement an outlier removal method [👨🏫 Teacher: Бернгардт Олег Игоревич] {5️⃣ Semester} (Data analysis)
Topics: Normal distribution, Functions of Random Variables
This repo contains various projects and assignments I worked on in my Economics Courses
SUTD ISTD 2021 50.034 Introduction to Probability & Statistics 1D Project
Exercise solution to the Probability Theory course
Simple tool for estimating frequencies of random variables.
Implemented algorithms from a numerical stochastic methods university course
This repository houses a comprehensive Graphical User Interface (GUI) tool designed for analyzing and visualizing random variables (RVs) and random processes (RPs). The tool allows users to input specific values and parameters of RVs and RPs, enabling the generation of statistical data, graphical representations, and calculations related
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