There is a very large amount of homework for what should be an introductory course. To make things worse, the homework is rather difficult and time consuming. To make things even worse, the material tested on the midterm is pedantic, and some questions require you to know minute details of the language that wouldn't be useful in any meaningful context.

Professor Tsiang is such a great professor! This is a hard course but he truly cares about his students and wants to make sure everyone is understanding the concepts. His exams and homework are very fair, but challenging at the same time so you end up learning a lot in a short amount of time, and he and the TA (the hot one) are always willing to help. He is very approachable during office hours or on Campuswire where you can ask homework questions or lecture questions and he, the TA, or other students can answer. He is one of the best professors I have had at UCLA because he cares about his students and wants to make sure his class is fair and doable but also wants to challenge his students. I learned a lot from this course about RStudio and about myself as a student and it is all due to Professor Tsiang and TA Edouardo. While we are here let me also give a mini-review of Edouardo, the TA, who is also very understanding and knowledgeable on the subject. The class has changed a lot in the last few quarters so I would ignore previous reviews because the class is very different now in my opinion. Edouardo and Professor Mike are on your side, even when the course gets hard, they are not out to get you. They are both funny and it was a pleasure having them as instructors for this course because they taught their students not only the basics of RStudio but also gave us great mini TedTalks on study tips and life tips. This now has turned into me raving about them but I have nothing but good things to say about this course and them.

Okay maybe this class was an easy class before but for this quarter it clearly is not. Just as the review below says, this class is actually fast-paced and if you're a total coding beginner like me, you might have a difficult time keeping up. Also, the homework is really hard. The second midterm is the day after tomorrow and the practice midterm was just posted today. Also, there is one homework consisting of 26 questions due that day as well. Besides the homework, the way this class is designed is just very confusing. No solutions for the homework is posted. Homework is based on some mysterious rubric (which is also posted). You'll lose points for not writing a response in text, solutions not being efficient... I just feel tired at this moment. Don't be lied by the high rating of the professor and the high A rate. Maybe it was true for the previous quarters, but I believe the A rate will be much lower this quarter. As for the professor, I believe Mike is a nice guy but I didn't feel his lecturing skill is as good as his rating (don't get me wrong he still gives good lectures).

First, a bit of background about myself-
I'm a UCLA student currently leading a software-heavy engineering team (20+) with several years background in coding (Python, C++, Java, R, Mathematica, etc) and experience in several different development environments.

This class is too much. When the Stats dept changed the scoring metric so this becomes a weedout class, they also heavily affected the core meaning of this class. Mike is an, overall, good professor who seems to care about his students (although not enough). His constant virtue sigaling is a huge problem, however- when you assign a heavy final project and a heavy homework set during thanksgiving, you don't care about your students' well being that much.
Additionally, Jake (the lead TA) seems to delight in taking away points from his students, frequently grading on pedantic issues and 'stylistic choices' (I've issued several documents to my team detailing "proper style" and would never dream to be as controlling as him).

Overall, however, it speaks to the decline of Statistics at UCLA when the lower level classes are being squelched this badly. Don't take this class if you can help it.

Real d*ck move by the stats department to try to turn this class into a weeder. Don't believe any reviews from before Fall 2019. Mike and Jake are both terrible humans. Don't take this class if you can help it.

I think students have talked a lot about the hardness of this course. The experience I want to share is about Michael's referring students to the Dean's office. During that quarter, about 50 people are referred to the Dean's office, which is unreasonable for a class. Did every referred student commit serious issues? Not really; after my case was closed, my problem was reading the syllabus carelessly instead of copying code. In a coding course, it's typical for students to Google the challenging assignment problem as far as students understand them and write the answers in their own words. Such a learning method is different from copying code.
Furthermore, one of my friends was accused of an offense he had never done. In Michael's email, he said his action is the best for students' long run; the truth is we don't appreciate such rude movements. Let me tell you the consequence of such unreasonable referring. Once Michael refers the student to the Dean's office, removing the 'DR' notation on the student's transcript will take another quarter, no matter whether the student commits something or not. The 'DR' notation can be a disaster for the students who want to apply to graduate school during this period. Even if you receive an A after your case is closed, it won't help anymore. Your dream school can reject you, or you must wait until next year to apply because there is a 'DR' on your transcript.
I suggest avoiding this course during the fall since the unreasonable 'DR' can kill your future path.

Mike was the best professor I have had at UCLA. His lectures are extremely clear and organized. I came into this class with no programming experience and left with a great understanding of R. It is evident that he cares a lot about each of his students and focuses more on your learning than your overall grade. I wouldn't say this is an easy class but you will definitely learn a lot. Edouardo the TA is also super cool and very different from the old TA who a lot of the old bad reviews are about. He always upvotes my replies on Campuswire (even when no one else does). Overall a great experience.

This class has gone through a lot of changes, but I believe that this past quarter had the best iteration of the course. TLDR: This class is very good! You just have to put in the time and make an effort to go to office hours and practice outside of class. This class provides a very strong foundation in R and prepares you for the 101 & 102 series, other classes, and even research! If you read the past reviews, just go into the class with an open mind and don't stress! I took this along with 3 other STEM classes and found this to be a decent time-sink, but rewarding and not too stressful.
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STRUCTURE: ~8 homework assignments, 2 midterms, Campuswire participation, discussion attendance, and a final (additional final project was cancelled)
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INSTRUCTION: Professor Tsiang and our TA Edouardo are extremely knowledgeable about R and statistics in general (he teaches 100C as well) and emphasize student learning entirely over stressing about grades. Some may interpret his constant concern as disingenuous, but if you go to OH and/or talk to him outside of class, you will see that it is genuine! They say that you don't need any coding experience but I HIGHLY recommend acquainting yourself with some form of programming beforehand, it doesn't have to be much or even a whole course like CS 31 or PIC 10A. Some folks were struggling with functions and control flow late into the quarter which surprised the instructors. In each asynchronous lecture, Professor Tsiang explained topics in detail and performed examples. These were mainly covered in lecture note PDFs, but there's some conceptual questions for you to think about on your own; I highly recommend you try to do each one and go to OH if you can't think of a solution. R has a few intricacies such as vectorization (which makes many for-loops you would typically make in C++ or Python inefficient and actually discouraged) and indexing from 1 which make previous knowledge start to hurt more than help, so again, go to office hours! In discussion section, Edouardo went over difficult concepts and commonly-made mistakes on past and current homework assignments. The LAs also had their own office hours and were very helpful when going over your own exams and homework assignments.
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EXAMS: It seems like the grading and type of questions are much less strict than previous quarters. The average scores were in the 70s or 80s which is typical of any slightly difficult STEM lower division course. They include function-writing, finding and fixing errors in code, and a tiny bit of data analysis. These exams were quite stressful but as long as you have been paying close attention to lecture and doing the homework, you should be able to get a decent score. There is a massive curve at the end in which about half of the class gets some form of an A, so don't expect to need a 90%+ or third-quartile (or even median sometimes) score on exams to get a good grade in the class. Don't stress and try to focus on learning the material, not achieving an A. If you want an easy A and aren't concerned about having a solid foundation in R, there's nothing wrong with that! I just wouldn't recommend this class however.
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HOMEWORK: These are similar to exam questions, except they are graded on completion and effort! There are easy-intermediate-optional hard questions on almost every assignment, however once they're graded only the easy solutions are posted. This was a bit annoying, but it forces you to think about your code and maybe go to OH to find out what's wrong with it. I liked that a lot of the questions made you create your own versions of base functions in R because it makes you really understand the base functions and their intricacies. The homework may take a few hours to do, so start early and take breaks. Use Campuswire to discuss the questions you are allowed to, it really helps! P.S. Asking questions and answering other people's questions gets you free points, and if you do it enough then a tiny bit of extra credit!
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I hope whoever reads this finds this useful and accurate; details such as exam structure and lectures will be different since I took this online during the pandemic. Best of luck!

** During the pandemic **
I really liked Mike, his lectures, and his detailed notes. It's clear that everyone involved (the professor, the TA, and the LA) put a lot of time, effort, and straight up love into running and fixing up this class. The Campuswire environment felt super student-friendly, and I felt like I learned a lot without too much stress -- I just followed along with the lectures at the end of every week, did the homework, and scored in Q4 and Q3 on the two midterms. These guys are Gs are did a really good job organizing the class this quarter, especially for the pandemic. I will 100% try to take another class with Mike if I can :)

I do not know how his lectures were like in the past, but according to my experience, professor Tsiang is definitely a professor who is underrated. His lectures are extremely structured and clear, with notes that remind you of the content of the lectures even after the quarter ends. It is true that some of the questions in the homework are tests are tricky, but they really really give you a deep understanding of R. He has made my 102 series a lot easier. Also, he curves really generously and provides different grading schemes. Do not be frightened by the absolute scores in the tests, focus on what you have learnt, and enjoy your stats 20 with professor Tsiang. Highly recommend!