# Course Reader for CS109

CS109

Department of Computer Science

Stanford University

Jan 2023

V 0.9

**New in Win 2023**:

- Digital Vision Test.
*Jan 3rd 2023* - Random Shuffles.
*Jan 2nd 2023* - Bayesian Carbon Dating.
*Dec 28th 2022* - Night Sight.
*Dec 28th 2022* - Algorithmic Analysis.
*Nov 11th 2022* - MLE Pareto.
*Nov 14th 2022* - Differential Privacy.
*Nov 14th 2022*

*Acknowledgements: This book was written by Chris Piech for Stanford's CS109 course, Probability for Computer scientists. The course was originally designed by Mehran Sahami and followed the Sheldon Ross book Probability Theory from which we take inspiration. The course has since been taught by Lisa Yan, Jerry Cain and David Varodayan and their ideas and feedback have improved this reader.*

*This course reader is open to contributions. Want to make your mark? Keen to fix a typo? Download the github project and publish a pull request. We will credit all contributors.*

Folks who have contributed to editing the book: GitHub Contributors. This includes Logan Bhamidipaty, Jonatan Pérez, Bobby Abraham, Tim Gianitsos, Yogi the Curious, Thanawan “Ly-Ly” Atchariyachanvanit, Kunal