PyStatsV1 documentation

Welcome to the documentation for PyStatsV1 – chapter-based applied statistics examples in plain Python, mirroring classical R textbook analyses.

Students (recommended): install from PyPI and start the Workbook

If you’re a student (not a developer), the easiest path is to install the Workbook bundle from PyPI and let the CLI create a local copy of the labs for you.

python -m pip install "pystatsv1[workbook]"
pystatsv1 workbook init --dest my_workbook

Then run the built-in checks as you work:

cd my_workbook
pystatsv1 workbook check

If you’re on Windows 11 and this is your first time installing Python, start here: Windows 11 setup (students).

Lightweight install (no Workbook checks)

If you only want the core helper package (without the Workbook checks bundle), you can install the base package directly from PyPI:

python -m pip install pystatsv1

Developers / Contributing

If you want the full chapter-based labs (simulators, scripts, Makefile targets, and tests), clone the GitHub repository and install in editable mode:

git clone https://github.com/pystatsv1/PyStatsV1.git
cd PyStatsV1
python -m pip install -e .

See Getting started and Contributing for the contributor workflow.

Workbook – Student Labs (recommended starting point)

PyStatsV1 Workbook

Track A – Applied Statistics with Python (Regression)

Track B – Psychological Science & Statistics (Psych track)

Track C – Problem Sets & Worked Solutions (Psych track)

Track D – Business Statistics & Forecasting for Accountants