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https://github.com/danmadeira/algoritmos-estatistica-python

Demonstração de Algoritmos de Estatística em Python
https://github.com/danmadeira/algoritmos-estatistica-python

algorithms data-analysis data-science python statistics

Last synced: 4 days ago
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Demonstração de Algoritmos de Estatística em Python

Host: GitHub
URL: https://github.com/danmadeira/algoritmos-estatistica-python
Owner: danmadeira
License: gpl-3.0
Created: 2022-04-03T14:50:38.000Z (over 2 years ago)
Default Branch: main
Last Pushed: 2022-04-03T14:52:06.000Z (over 2 years ago)
Last Synced: 2023-10-20T07:51:33.080Z (about 1 year ago)
Topics: algorithms, data-analysis, data-science, python, statistics
Language: Jupyter Notebook
Homepage:
Size: 125 KB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE.md

Awesome Lists containing this project

README

## Demonstração de Algoritmos de Estatística em Python

Esta é uma demonstração de funções que implementam alguns cálculos estatísticos. Os algoritmos que representam as fórmulas estatísticas estão escritos em uma estrutura simples e semelhante a aplicação pura das respectivas fórmulas, para deixar o código o mais limpo possível, e assim, didático.

Até o momento, estas são algumas das fórmulas estatísticas que estão presentes:

* Média Aritmética
* Média Aritmética Ponderada
* Média Geométrica
* Média Geométrica Ponderada
* Média Harmônica
* Média Harmônica Ponderada
* Média Quadrática
* Média Quadrática Ponderada
* Média Cúbica
* Média Cúbica Ponderada
* Média Desarmônica
* Média Desarmônica Ponderada
* Mediana
* Moda
* Desvio Absoluto Médio
* Desvio Absoluto Mediano
* Variância Populacional
* Desvio Padrão Populacional
* Variância Amostral
* Desvio Padrão Amostral
* Coeficiente de Variação
* Covariância Populacional
* Covariância Amostral
* Coeficiente de Correlação Populacional de Pearson
* Coeficiente de Correlação Amostral de Pearson
* Somatório dos Quadrados
* Somatório dos Produtos XY
* Z-score Populacional
* Z-score Amostral
* Três Desvios
* Amplitude
* Assimetria
* Curtose
* Quartis
* Desagrupar dados
* Agrupar dados

Obs.: As funções possuem versões para dados agrupados ou não agrupados e para dados amostrais ou populacionais. Ao final, há uma demonstração da execução das funções e, em alguns casos, há um comparativo com as funções disponíveis no Python.

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