" by Peter Gedeck, Andrew Bruce, and Peter Bruce provides the code and data to accompany the O'Reilly book of the same name. It is a foundational resource for data scientists looking to bridge the gap between theoretical statistics and practical data analysis using and Python . Core Repository Features

Example: data/simulated/heteroscedastic_simulation.csv — generated with y = 2*x + ε * x to teach WLS.

: Use the Exploratory Data Analysis notebook to see how statistics are applied to real datasets in Python.

The "Practical Statistics for Data Scientists" GitHub repository is a collection of code, data, and examples from the book of the same name by Peter Bruce, Andrew Gelman, and Kristian Lum. The repository provides a hands-on approach to learning statistics, with a focus on practical applications and real-world examples.

Not just mean/median — statistical EDA