Description: An introduction to probability theory and statistics, with an emphasis on solving problems in computer science and engineering. Probability and statistics is an important foundation for computer science fields such as machine learning, artificial intelligence, computer graphics, randomized algorithms, image processing, and scientific simulations. Topics in probability include discrete and continuous random variables, probability distributions, sums and functions of random variables, the law of large numbers, and the central limit theorem. Topics in statistics include sample mean and variance, estimating distributions, correlation, regression, and hypothesis testing. Beyond the fundamentals, this course will also focus on modern computational methods such as simulation and the bootstrap. Students will learn statistical computing using the freely available R statistics software: http://www.r-project.org/.

Class meetings: 3:40 - 5:00pm, Tuesdays and Thursdays in WEB L101

Instructor: Tom Fletcher
Office: 4686 WEB
Email: fletcher AT cs.utah.edu
Office Hours: 10:00am - 11:00am Mondays and 1:00pm - 2:00pm Wednesdays

Teaching assistants:

All TA Office Hours are in MEB 3115

Aishwarya Asesh
Office Hours: 4:30 - 6:00pm Mondays and Wednesdays

Yash Gangrade
Office Hours: 3:00pm - 4:30pm Mondays and Wednesdays

Atefeh Ghanaatikashani
Office Hours: 9:00am - 10:30am Tuesdays and Thursdays

Nipun Gottapu
Office Hours: 10:30am - 12:00pm Mondays and Wednesdays

Hang Shao
Office Hours: 1:00pm - 2:30pm Tuesdays and Thursdays

Announcements: We will use Canvas for class announcements. These may be time-sensitive, so make sure your Canvas notifications go to an email address that you check regularly. Also, make sure that notifications are set to be sent immediately. Find these settings in Canvas under "Account -> Notifications".

For Help: Email teach-cs3130 AT list.eng.utah.edu to send a question to the instructor and TAs.

Textbook: A Modern Introduction to Probability and Statistics: Understanding Why and How by Dekking, Kraaikamp, Lopuhaa, and Meester.

An electronic version of this book is freely available through the University! The website is here: http://www.springerlink.com/content/978-1-85233-896-1. To access the book you must be visiting this website from the campus network. Or if you are off campus, you can access it using VPN: https://vpnaccess.utah.edu/.

Why Study Statistics?