### CS1450, Fall 2018, taught by Professor Eli Upfal

Probability and statistics have become indispensable tools in computer science. Probabilistic methods and statistical reasoning play major roles in machine learning, cryptography, network security, communication protocols, web search engines, robotics, program verification, and more. This course introduces the basic concepts of probability and statistics, focusing on topics that are most useful in computer science applications. Topics include: modeling and solution in sample space, random variables, simple random processes and their probability distributions, Markov processes, limit theorems, and basic elements of statistical inference.

This course emphasizes both mathematical rigor and computing applications. Topics are similar to Statistical Inference I (APMA 1650) with more of a focus on modern applications and formal proof.

If you have any questions about the course, please email the HTA Zack.

### For more information:

- Carefully read the course syllabus (pdf) and grading policies (pdf).
- If you have questions, please post to the Piazza discussion site.
- If you want extra help, get a copy of Introduction to Probability, 2nd Edition, by Bertsekas and Tsitsiklis. Probability by Pitman is also recommended.