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Tue & Thu 3:40PM-5:00PM, ASB 220
Final Exam: Wednesday, April 30, 2025, 03:30pm – 5:30pm, Online Official Page
| Office | MEB 3466 |
| zhe at cs dot utah dot edu | |
| Teaching Assistant: | Qiwei Yuan (joshua.yuan at utah.edu) |
| Teaching Assistant: | Keyan Chen (u1466725 at utah.edu) |
| Teaching Assistant: | Yile Li (yile.li at utah.edu) |
| Teaching Assistant: | Jingyi Long (u6046121 at utah.edu) |
| Office Hours | Instructor: Tue & Thu 5:00pm - 6:00 pm MEB 3466 |
| Qiwei Yuan: TBD | |
| Keyan Chen: TBD | |
| Yile Li: TBD | |
| Jingyi Long: TBD |
This course provides a calculus-based introduction to probability and statistics. It covers fundamental concepts and computational methods, preparing students for careers in electrical and computer engineering, computer and data science, and software development. Additionally, it lays a foundation for advanced study in machine learning and artificial intelligence.
The major textbook for this course is A Modern Introduction to Probability and Statistics Understanding Why and How [Online]. For a bit more in-depth study, you are referred to All of Statistics, A Concise Course in Statistical Inference[Online]
The grades are based on the following components:
Assignments must be electronically submitted through Canvas by midnight of the due date. Instructions about submission will be given in each assignment.
All assignments should be submitted by the deadline. If the deadline is missed, the late submissions will have 10% penalty. In every subsequent 24 hours, the late submissions will loose another 10% credicts. For example, a 10 points assignment will have 2 points penalty, if it is submitted 30 hours late. However, if the assignment is not turned in until the other assignment have been graded and returned or 48 hours after the deadline, 0 grade will be given.