Information Theory, Inference, and Learning Algorithms is a textbook with related resources by David MacKay.
IMS
Introduction to Modern Statistics is an open college-level textbook covering multivariable relationships and simulation-based inference.
About IMS
IMS is Introduction to Modern Statistics, an open college-level textbook highlighting multivariable relationships and simulation-based inference. This GitHub page holds the book's source files, including chapter files, data, exercises and solutions, while the readable e-book is hosted on Netlify with separate addresses for the second and first editions.
Key features
- College-level statistics text emphasizing multivariable relationships
- Covers simulation-based inference including bootstrapping and randomization
- Includes chapters on regression modeling and inferential modeling
- Provides exercises with separate exercise-solutions files
- Includes datasets in repository data folder
- Maintains separate hosted versions for first and second editions
Best for: College students and instructors seeking an open textbook on multivariable relationships and simulation-based inference.
Good for
- Open college-level textbook focused on multivariable relationships and simulation-based inference
- Readable second and first editions hosted separately on Netlify
- Source includes chapter files, data, exercises and exercise solutions
IMS at a glance
- Website
- github.com/OpenIntroStat/ims
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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IMS FAQ
Where is the second edition of IMS?
At https://openintro-ims.netlify.app/
Where is the first edition of IMS?
At https://openintro-ims1.netlify.app/
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