Hypothesize
The facts below are what the maker publishes about Hypothesize, checked and dated. Our editors have not written about it yet.
The facts
Each one read from Hypothesize's own pages, with the date it was checked.
What it does
- Academic citation
- The site requests that academic users cite Campopiano and Wilcox's 2020 Journal of Open Source Software article.checked 11 Oct 2026
- Citation
- The home page gives a 2020 Journal of Open Source Software citation with Allan Campopiano and Rand R. Wilcox as authors.checked 11 Oct 2026
- Data import formats
- Pandas DataFrames or Series; CSV via Pandaschecked 23 Sep 2026
- Dependencies
- The listed dependencies are Python 3.6 or newer, NumPy, Pandas, SciPy, and more-itertools, installed automatically with the installation command.checked 11 Oct 2026
- Deployment
- desktopchecked 23 Sep 2026
- Error control
- Family-wise error can be controlled with sequentially rejective methods.checked 11 Oct 2026
- Estimator options
- Where applicable, tests can use estimators such as the mean, median, trimmed mean, winsorized correlation, and percentage bend correlation.checked 11 Oct 2026
- Estimators
- Where applicable, tests let users specify estimators such as the mean, median, trimmed mean, winsorized correlation, and percentage bend correlation.checked 11 Oct 2026
- Examples
- The overview says one-click, ready-to-run examples are available for every top-level function.checked 11 Oct 2026
- Installation
- The package can be installed with pip using `pip install hypothesize`.checked 11 Oct 2026
- License
- Hypothesize is licensed under the BSD 3-Clause license.checked 11 Oct 2026
- Methods
- The library brings robust statistical methods based on Rand R. Wilcox’s WRS package to Python.checked 11 Oct 2026
- Notable function limit
- The function reference says some documented tests currently support only `trim_mean` as their measure-of-location estimator.checked 11 Oct 2026
- Notable limitation
- The function reference says `l2drmci` cannot handle unequal sample sizes when `pairwise_drop_na` is false.checked 11 Oct 2026
- Notebook integration
- The GitHub README says each statistical test can be launched in Deepnote’s hosted notebook environment with sample data.checked 11 Oct 2026
- Purpose
- Hypothesize is a Python library for robust statistics that compares groups and measures associations.checked 11 Oct 2026
- Regression models
- Nochecked 23 Sep 2026
- Requirements
- The listed dependencies are Python 3.6 or newer, NumPy, Pandas, SciPy, and more-itertools; the page says they install automatically with the pip command.checked 11 Oct 2026
- Scripting support
- Yeschecked 23 Sep 2026
- Statistical designs
- It supports single- and multi-factor designs, including independent, dependent, and mixed groups.checked 11 Oct 2026
- Statistical tests
- Yeschecked 23 Sep 2026
- Support
- The home page directs users to GitHub Issues for questions and bug reports.checked 11 Oct 2026
The company
- Founded
- 2020checked 19 Oct 2026
Money
- Free plan
- Yeschecked 23 Sep 2026
