AI-Assisted Statistics for Data Scientists: 50+ Essential Concepts Using R and Python by Peter Bruce, Andrew Bruce, and Peter Gedeck Publisher: O'Reilly Media; 3rd edition (June, 2026) ISBN-13: 979-8341666283 Buy on Amazon Errata: http://oreilly.com/catalog/errata.csp?isbn=0642572242428

Table of Content

1. Exploratory Data Analysis
2. Data and Sampling Distributions
3. Statistical Experiments and Significance Testing
4. Regression and Prediction
5. Classification
6. Statistical Machine Learning
7. Unsupervised Learning
8. Neural Networks
9. Deep Learning
10. Generative AI and Large Language Models (LLMs)
11. Caveats and Concerns

Code Documentation

The R and Python source code from the book is available as browsable and searchable webpages containing all code, output, and figures from the book.

• R code
• Python code

Download

Download the data and source code as ZIP archives:

• data.zip — the data files used throughout the book
• python.zip — the Python source code
• R.zip — the R source code

See also

Code repositories for first and second edition:

• First edition: https://github.com/andrewgbruce/statistics-for-data-scientists
• Second edition: https://github.com/gedeck/practical-statistics-for-data-scientists