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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["confidence-intervals","data-analysis","hypothesis-testing","null-hypothesis","python","r","robust-statistics","significance-testing","statistics","stats"],"created_at":"2025-06-09T15:01:12.825Z","updated_at":"2026-03-09T21:02:52.850Z","avatar_url":"https://github.com/Alcampopiano.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Hypothesize \u003ca href=\"https://Alcampopiano.github.io/hypothesize/\"\u003e\u003cimg align=\"right\" src=\"https://github.com/Alcampopiano/hypothesize/blob/master/docs/docs/img/vp_inv.png\" height=\"50\"\u003e\u003c/img\u003e\u003c/a\u003e\n\n[![status](https://joss.theoj.org/papers/caf4095b3cdcc3adbb0252c995d59926/status.svg)](https://joss.theoj.org/papers/caf4095b3cdcc3adbb0252c995d59926)\n![tests](https://github.com/Alcampopiano/hypothesize/workflows/tests/badge.svg)\n[![PyPI version](https://img.shields.io/pypi/v/hypothesize?style=flat-square)](https://pypi.org/project/hypothesize/)\n[![PyPI - Downloads](https://img.shields.io/pypi/dw/hypothesize?style=flat-square)](https://pypistats.org/packages/hypothesize)\n[![license](https://img.shields.io/pypi/l/hypothesize?style=flat-square)](https://github.com/Alcampopiano/hypothesize/blob/master/LICENSE)\n\nA Python package for hypothesis testing using robust statistics\n\n## Basic Example\n\n### A robust measure of association with winsorized correlation\n[\u003cimg src=\"https://deepnote.com/buttons/launch-in-deepnote-white-small.svg\"\u003e](https://deepnote.com/launch?name=wincor\u0026url=https://github.com/Alcampopiano/hypothesize/blob/master/examples/wincor.ipynb\n)\n\n```python\nfrom hypothesize.measuring_associations import wincor\nfrom hypothesize.utilities import create_example_data\n\n# creating an example DataFrame with columns \"cell_1\" and \"cell_2\"\ndf=create_example_data(2)\n\nresults=wincor(df.cell_1, df.cell_2)\n\n# returning the correlation, number of observations, p-value, and winsorized covariance\nprint(results)\n{'cor': 0.11, 'nval': 50, 'sig': 0.44, 'wcov': 0.01}\n```\n\n## Documentation\n:book: Please visit the [Hypothesize documentation site](https://Alcampopiano.github.io/hypothesize/).\nNote that each statistical test in the can be launched \ndirectly in [Deepnote's](deepnote.com) hosted notebook environment—complete with sample data \n(as shown in the example above 👆). \n\n## Citing Hypothesize\n\n[![status](https://joss.theoj.org/papers/caf4095b3cdcc3adbb0252c995d59926/status.svg)](https://joss.theoj.org/papers/caf4095b3cdcc3adbb0252c995d59926)\n\nIf you use Hypothesize in academic work, please use the following citation:\n\nCampopiano, A., \u0026 Wilcox, R. R. (2020). Hypothesize: Robust Statistics for Python. \nJournal of Open Source Software, 5(50), 2241, https://doi.org/10.21105/joss.02241\n\nBibTex:\n\n```bib\n@article{Campopiano2020,\n  doi = {10.21105/joss.02241},\n  url = {https://doi.org/10.21105/joss.02241},\n  year = {2020},\n  publisher = {The Open Journal},\n  volume = {5},\n  number = {50},\n  pages = {2241},\n  author = {Allan Campopiano and Rand R. Wilcox},\n  title = {Hypothesize: Robust Statistics for Python},\n  journal = {Journal of Open Source Software}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falcampopiano%2Fhypothesize","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falcampopiano%2Fhypothesize","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falcampopiano%2Fhypothesize/lists"}