A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python

Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that are very important to Data science domain and its application using Python. Learn about Numpy, Pandas Data Frame.

Pure python statistic tools for high energy physics.

Strategies for analyzing the distribution of datasets, switching the data towards a normal distribution testing different manual transformations and Box-Cox transformation.

CSE303 Lab Problem Solving apart. This course is really helpful for real life.

Library for calculating statistical distributions, written in pure Python with zero dependencies.

Examples on Descriptive Statistics and Linear Algebra in Python

Exercise Files for Statistical Analysis in Data Science Using Python

Python ile basit derecede veri istatistiği yapmak için bu repo oluşturuldu.

This module covers the formal topic of statistics and its relevant concepts. It covers a number of theoretical discussion points and examples and hands-on coding activities to help understand theory.

"Applied Data Science Program - Leveraging AI for Effective Decision Making" course by MIT-PE

Métodos Estatísticos com Python.

Python implementation of a toolkit for researchers studying electoral polarization. Features ideological and affective polarization analysis, issue salience modeling, and comprehensive statistical validation following Ginzburg's (2024) framework. Jupyter Notebook based.

Repositório destinado a documentar o conhecimento em Python sobre estatística, mais aprofundado em frequências e medidas, utilizando as bibliotecas Numpy, Pandas, Seaborn e Scipy.

This repository showcases a collection of well-documented projects focused on Hypothesis Testing and both Descriptive and Inferential Statistical analysis. It includes practical implementations of statistical tests such as t-tests, ANOVA, Chi-square, Mann-Whitney U, and correlation analysis, alongside summary statistics and visual insights