I took this class in summer 2019, the slides he used was very clear and easy, but the homework was really unfairly hard and the tests were tough. It's impossible for a student who just finished stats 20 to write two games and other homework like that. I think the TA JAKE made up the homework, he just wanted to show how talented he is. Avoid this professor and the TA JAKE. If you can, just change the major.

Don't take Stats 20 with Professor Tsiang who always has Jake Cramer as TA!!! I dropped this course on Week 2. The workload was unreasonablly large, and all homeworks and exams were very difficult. Strategies for problems on weekly homework were not taught in class, and they needed great amounts of time.

Michael Tsiang provides notes that are very clear regarding R syntax and gives a good overview of R in general, and you should be able to do some simple data projects on your own after this class. His lectures are essentially going through the notes and code on RStudio and explaining slightly more in depth, but not by much. The homework was manageable (medium to hard difficulty), but they are graded based on optimization as well--you will get docked points if your code doesn't solve the problem in the quickest way, which is not something considered in CS 31 or 32. Tsiang was more helpful when I asked him questions in person.

On the negative side, he was slightly passive aggressive in class. He threatened to tank everyone's grades when someone took a photo of his slides during lecture against his wishes. The exams are difficult in that you have to be extremely familiar with the output formats of different inputs, which I don't think is very relevant to real-day usage where you can tinker around with code and see the output, but might be relevant to coding interviews. Most people found the exams hard, and I scored a B to B+ on both midterms and the final and got an A in the class, so it was definitely curved.

Overall, it's a good overview of R, but the exams and instructor are slightly off-putting. It'll be helpful to work through the problems and study with peers.

Note: This review is for Winter 2021, a quarter conducted remotely for this class.

I took STATS 199 with Professor Tsiang because I enjoyed his STATS 20 class and him as a professor and person. He let me take the lead for my directed research--I did mine on fantasy football analysis (in fact, he didn't know much about the topic, just the analysis I was performing). In terms of what is required, the only thing I had to submit was a final research paper.

Professor Tsiang allowed me to meet with him on my schedule. I could meet as often (or as little) as I needed, and he helped me with a few questions I had about the process. I met on a weekly basis (for the most part) to give him updates throughout the quarter.

TL;DR: Professor Tsiang let me run the course; he served as a mentor as I worked on my research. Ultimately, this course is about the student more so than the professor.

If you're here to find an easy class, go find another class lol, this will definitely take some chunk of your week to do the hw. I'll be honest, I like Michael and wow surprisingly unlike the reviewers here, Jake too. I took this when crap hit the fan with COVID. Class wasn't too hard, unfortunately I wasn't as focused as I'd like to be because you really do learn a lot in this class. If you engage with Jake or Michael during office hours or through questions on discussion boards, they will remember you! Michael's notes are very good and R has swirl which is an interactive command line platform that you go through each assigned chapter that Michael has designed. Our final project was made optional because of how hectic everything is and I am very grateful. I will say the best way to study for this class is to just plug in random crap into R and predict what the outcome is. You don't get to have R by your side during an exam and Jake expects you nail the basics. Having some computer programming experience is definitely preferred because how everything in R is stored is probably harder unless you understand that(although you'd just have to put in the effort to read more if you dont have experience). Miles sometimes likes to be cryptic with his answers because he wants you to learn(that definitely frustrated me a lot), but as long as you show that you're trying, he'll "tell" you the answer if he sees you struggling a lot.

I love Mike omg he's one of my favorite professors in the stats dept. He really cares about his students and wants us to deeply understand the material that he's so passionate about (he literally said every method we learned in this class was his favorite lol). I also had him for Stats 20 in Fall 2019 (which is when the homework/tests changed although it was still a great class, most people just complained cause of grading and making you think critically in a different way imo). Mike's 102C is more on the theoretical side than Prof Miles Chen, but there is still programming in R for simulations and sampling. Def brush up on 100B as you'll need it. Mike is helpful in OH and on Campuswire, and we got 1% EC for Campuswire or attending discussions (grading scheme 40% HW 60% final). He gave us 48 hours on our take home final (no internet, only class notes) which was incredibly generous. His homework and exams are just extensions of his lecture slides. Lectures were prerecorded and during our "lecture time" it was basically OH. Would recommend taking a class with Mike if you can!

Look, I hear Stats 13 is the easiest pre-req for LS majors. I am usually an A student, and was expecting this class to be a breeze. But, due to online learning, Tsiang made his exams a lot harder than it was in person (he used past exams as 'practice tests' even though they were wayyyy easier than the actual exams.) Recorded lectures were pretty straight forward, and I thought that I was well-versed in the material. Fast forward to Exam 1, I got a 77% (class average was 78%) and I was shook. Most questions were short answers, so I got many partial credit, and only got 1 multiple choice answer wrong. For the final I got a 75% (have no idea what was the class average), but same deal. To be fair, the exams are open note that's why they are harder, but even then, I was surprised since I'd do very well on the homework. According to syllabus, I had an 85% in the class, but Tsiang adjusted the grading scale to fit distributions, so I ended up with an A-. I am not too upset, since I was expecting a B, but I wish I would have been prepared on how detailed I needed to be when it came to short answer questions. Also he bombarded us with lecture videos Week 5, and it was just a bit too fast-paced and it was frustrating. I had many peers feel the same way as well. But at the end of the day, I really liked Tsiang, he's a good professor and cares about his students, I just didn't have that much interaction with him due to chaotic home life and to be honest, laziness to attend office hours.

The practice midterms and exams are definitely not reflective of the actual midterm and final, which really threw me off since they were more difficult...almost ambiguously and confusingly difficult. Exams were hard and I get why Dr. Tsiang made it harder due to remote learning. Nothing can really prepare you for it since there's no "practice exams/midterms" for remote learning. Recorded lectures were long and he read from the slides but it was digestible and Dr. Tsiang just followed the textbook (that is not required!) I really appreciate Dr. Tsiang not mandating purchasing textbooks and materials for the course.

Aside from emails, the primary mode of correspondence for this quarter was a Discord server which I really didn't go on much except to clarify a few things that someone else already asked.

His love for Parks and Rec definitely permeates into the course, so if you're a fan, you'll appreciate the incorporation of the show into the work...if you're not, just nod and smile.

Labs are easy since the TA just uploads the video doing the lab step by step, question by question. No problems with that. Labs were probably the easiest thing to complete from this course.

This is a class many of y'all probably need to take, so just bite the bullet now and take it and hold on. Don't let go or fall off the wagon mid-quarter and don't let time slip away.

This was the worst class I took at UCLA. I changed it to P/NP because I literally thought I was gonna fail. The highest grade I got on an exam was 35%. Yes, in the end it was curved. But the stress/depression that this class caused me was not worth anything. The TA (I had Jake) was intimidating, not helpful whatsoever, and smug! The lectures were actually super clear and the notes were helpful so you'd think it would be straightforward! But it wasn't at all...it was like learning the ABCs in class then having to write your own code for ranked choice voting for homework. For an introduction to programming class, it was absurd. They said you didn't need any prior experience coding to excel in the class but this was not the case at all. Not to be dramatic but I wouldn't recommend this class to my worst enemy

I took Stats 20 for the Social Data Science Minor. A few things to start are that this is NOT a stats class. It is strictly learning to program with R. I have taken multiple AP classes for Computer Science and I understand how to code at a beginner/intermediate level. The class consisted of weekly HW and quizzes. The quizzes were easy but the HW just didn't make sense. The HW was always extremely difficult and required a lot of time dedicated to complete these questions that didn't really mean anything since the HW is completion credit. The tests were alright and I received consist low 70s but finished the class with a B+. The curve is extremely forgiving and its very achievable to get an A. I just didn't really practice enough. Professor Tsiang is a great teacher and resource but I just wont get how the hw took so long and didn't really translate on the tests.