I did not enjoy taking this class with Professor Wu. Prof W is a genuinely nice guy and he tries his best, but I thought he was just not a good lecturer. He was really unclear and so were his notes. Quizzes were graded on completion which provided good practice for the exams. Hw/projects were time consuming but graded leniently. What I had problem with was the exams: they tested on minute and seemingly trivial details, wordings can be confusing, and I thought they were hard. I thought I was going to fail the class and I ended up getting an A, so I suppose other students thought the tests were hard too. Chen is miles and miles better but his class is really hard to get, so if you do end up having to take Wu, my deepest apologies but it's definitely not end of the world (Sanchez cough cough).

Hard class, definitely prep early when you can.

You’ll be fine if you attend the lectures. You can have a cheat sheet for exams and I think there is a curve for the exams

In Stats 102A, Introduction to Computational Statistics with R, taught by G Wu, I found the lectures to be highly informative and engaging, particularly in their practical application of R programming. One area for improvement could be in providing more diverse examples during lectures to cater to different learning styles. The combination of lectures, readings, and homework assignments effectively prepared me for the tests, ensuring a comprehensive understanding of computational statistics. The grade I received in the course was in line with my expectations, reflecting both the effort I put in and the effective teaching strategies employed. Overall, the course met my educational objectives, allowing me to gain a solid understanding of computational statistics as applied in R, which was exactly what I sought from this class.