Discrete probability models. Review of discrete and continuous probability. Conditional expectations. Simulation techniques for random variables. Discrete time stochastic processes: random walks and Markov chains with applications to Monte Carlo simulation and mathematical finance. Introduction to Poisson process.
4
UnitsOptional
Grading1, 2
PasstimeNone
Level LimitLetters and science
CollegeHer tests are content she teaches in lecture. She doesn't purposely make it much harder like how some other professors do.
Easy course if you follow her lecture!
She's honestly kind of adorable. She genuinely enjoys when someone in the class gets the material, she's a good lecturer. Homework is super doable and her lecture slides are annotated very well.
FOR 160A: Very good and sweet teacher. I came to an office hour 30 minutes after it was done and she was still in there helping people and then helped me. Though the class could be done just by looking at the notes online and showing up to section, she is still a great lecturer. Midterm and Final were easy, just like the notes, and homework.
Overall nice professor, she was new. One quiz was dropped and majority of the later quizzes were fair. Midterm was extremely fair, but the final was rough. She stumbled and made a lot of mistakes during lectures and had to be corrected. Did not learn much in lecture, but overall was a decently fair class. It was her first quarter teaching though.