Hypothesize

A Python package for hypothesis testing using robust statistics

Basic Example

A robust measure of association with winsorized correlation

from hypothesize.measuring_associations import wincor
from hypothesize.utilities import create_example_data
# creating an example DataFrame with columns "cell_1" and "cell_2"
df=create_example_data(2)
results=wincor(df.cell_1, df.cell_2)
# returning the correlation, number of observations, p-value, and winsorized covariance
print(results)
{'cor': 0.11, 'nval': 50, 'sig': 0.44, 'wcov': 0.01}

Documentation

Please visit the Hypothesize documentation site.
Note that each statistical test in the can be launched
directly in Deepnote’s hosted notebook environment—complete with sample data
(as shown in the example above 👆).

Citing Hypothesize

If you use Hypothesize in academic work, please use the following citation:

Campopiano, A., & Wilcox, R. R. (2020). Hypothesize: Robust Statistics for Python.
Journal of Open Source Software, 5(50), 2241, https://doi.org/10.21105/joss.02241

BibTex:

@article{Campopiano2020,
  doi = {10.21105/joss.02241},
  url = {https://doi.org/10.21105/joss.02241},
  year = {2020},
  publisher = {The Open Journal},
  volume = {5},
  number = {50},
  pages = {2241},
  author = {Allan Campopiano and Rand R. Wilcox},
  title = {Hypothesize: Robust Statistics for Python},
  journal = {Journal of Open Source Software}
}