I decided for my reviews now I will now justify my scores for each of the components as well as a more extensive review:

Number Score Overview:
Easiness: 5 - Class content is not that difficult, exams are fair (NOTE: Took AP Stats in Highschool)

Clarity: 5 - He is very clear and great at explaining the statistical concepts

Workload: 5- The workload is not that bad, homework assignments can sometimes be long but not too bad, but it wasn't something completely unmanageable.

Helpfulness: 5- Mike was super helpful his office hour as well as the TAs. There was alot of support in that class to get the help you need.

Overall: 4- Overall this class was fine, I was a little bored but that's probably because I had learned the content before and it was very slow paced. I hated the labs, I did not learn anything and probably will forget the few things I remember about r. Content is interesting but go over less stuff compared to AP Stats.

Extensive Review:
Professor: Mike is a decent professor. He is really nice and really cares about your mental and emotional wellbeing. He is great at explaining things and he can be pretty funny if that's your sense of humor.

Class: The class is fine, a normal introductory statistics class. If you took AP Stats in highschool its pretty much the same thing except with less content. The main difference is that AP Stats covered more topics and focused more on theoretical stuff while this class focuses on what happens if theoretical conditions are not met and how to conduct these tests using simulation. The labs were pretty boring, did not learn much. I was just copying down whatever the TA. There will be coding on your exams so you should try harder on it than I did. The homework can be a bit long but for whatever reason, whoever is grading the homework is such a stickler for the smallest things. I would get the stupidest points marked off on my homework for the most random things. So just be aware of that.

Having taken AP Stats a couple years prior, I barely paid attention in this class and did all the (accuracy-graded) homework at 1:30 am with minimal repercussions aside from the usual self-inflicted carelessness. Seeing live the stats Ph.D.s' series of Canvas annotations notifications on my homework as they nitpicked my each and every mistake, misstep, and misoptimal calculation in the middle of the night gave me mild hypertension. I still don't get the policy of having graders separate from TAs for the homework and labs, since it's far more clumsy to learn from the mistakes from an upper div taker who isn't learning the same materials and methods in the class, but to be fair the only thing it really hurt was my pride. Lowest HW, Lab, and Quiz scores are dropped. The Campuswire condescension is kinda true, but not that terrible. The forum's used more like an all-around office hours. You don't need the textbook for this class since he just uses his slides as the content, and the slides are taken directly from the textbook anyway.
Tsiang gives lots of opportunities for people to get to know their classmates, which is more than I can say for almost any bio req lecture. Though few people came to lecture, the people that did saw each other a bit more, and we all kinda got to knew each other and interact with Tsiang if we needed clarification. I heard his 'Whine and Cheese Club' is also an option if you just want to talk more casually outside class, but I never really went so can't say much about it.
This professor notably exercises TA flexibility; anyone can decide to go to another TA or time slot instead if the one they're enrolled in doesn't work out. As someone in a 5-6pm discussion, having that option to go to the 4-5pm one instead freed a lot of time. Speaking of TAs, shoutout to Kaiwen for walking us through all the answers and apologizing when he interpreted the extra practice section wrong but extended the deadline for it, and was all around flexible during the flash floods. Also thanks to the teaching intern Josh for making practice tests for us, which I guess just aren't a thing Tsiang does normally. Other than that, this is a class you should put more effort than me into, but shouldn't be that stressful.

I have never met a more passive-aggressive person who has such a reputation for being nice. At first, Dr. Tsiang seems very sweet. He is super accommodating, makes a lot of jokes, asks students to call him Mike, has a no penalty late work policy, etc. He frequently makes pop culture references and really tries to relate to his students. In person, he's awesome. In contrast, he requires students to participate on campuswire for 2% of their overall grade. You need to reach red bird for full credit and eagle for extra credit. Here, he frequently belittles students for their answers, simply responding "incorrect." to their answers without explanation as to where their thinking is wrong. He hounds the site at all hours of the day, making it difficult to respond before him (he frequently complains that students answer after he already answered as if he didn't make participation required). He bemoans students not upvoting his answers when they upvote each other when he doesn't upvote students' answers. He berates students for not citing his slide deck when answering questions as if we have time to memorize where every piece of information is. I have never felt as unwelcome to participate in a class as here, and I had Dr. Scerri for a chemistry class. It feels as if Dr. Tsiang has this expectation of gratitude for his niceness, which makes it seem fake. That said, this class is criminally easy if you took AP Stats. Just reading the slides is sufficient to understand what is going on if you just need a refresher, so I would say going to lecture isn't necessary. If you're new to stats, I would at least watch the bruincast on 2x speed. The homeworks are much longer than Dr. Kim's, but they are still manageable and take 1-3 hours a week. The labs are tedious, but the TAs give you the answers, so don't worry if you've never had to code. The midterm and final are very easy as long as you know the basics of the material an are able to differentiate between different types of tests. I think the most challenging part of this class is being able to know the difference between when to use a single mean/proportion, two means/proportions, and regression.

TL;DR: Dr. Tsiang can be passive aggressive and mean to students over campuswire, but he is nice in person, and the class is very easy with lenient grading.

Overall, Mike is a great teacher. His notes, lectures, slides were super helpful and really easy to understand. However I felt like it was really hard to ask questions in person and even on campuswire. He would respond really passive aggressively and make students feel discouraged a lot. Overall its a good class

This class gave me the worst anxiety and panic out of my four classes for the quarter. As someone who has never coded before, the learning curve is quite steep as Professor Tsiang shoves in a lot of content. Additionally, homework takes a long time and nearly drove me to tears several times. However, I would say Tsiang genuinely cares for the students in this class. Besides OH (which he offered both in-person and online), he was also chronically on Campuswire answering our questions and had his LAs arrange a study session before each exam. He won't give answers straight away but it's still helpful nonetheless.
At the end of the day, I would choose Professor Tsiang again as my introduction to R as I did learn a lot from this class, but I would caution upcoming students to take this during a less-busy quarter so they don't feel overwhelmed all the time.

The content of this class is tough (easier if you already have coding experience). Homework and exams were difficult, however Mike places a huge emphasis on learning and not on worrying about grades. As a result, even with low exam scores and difficult homework, the class is curved very generously at the end. I would highly recommend taking this class with Mike as you can prioritize learning over grades, something a lot of classes nowadays lack.

I would overall recommend this class because I feel like the way the class was structured was really beneficial for learning without worrying about grades and gpa. The homework was graded on completion(with clear effort) and homework was worth a large percentage of your overall grade. The homeworks were manageable and really did allow me to exercise all I learned in class. The professor is truly very kind and understanding, and this class never gave me stress because it felt like a safe learning space. :)

As a Psych major pursuing a Computing Specialization, this was my first coding course. Hands-down, this was the most applicable course I've taken at UCLA so far. While it is definitely challenging, it is extremely rewarding because you learn so much; Professor Mike and the TAs are super supportive and understanding, as well. Prior to this course I already had some experience with using R for basic data organization, graphics, and statistics, but I still found the course soooo helpful and interesting because it really helped me begin to understand the deeper intuition behind everything in R. Homework-wise, some of the assignments were very long and difficult, but as long as you made an honest effort you would get 100% on them (they're completion-based). Exam-wise, the tests were challenging and relatively unpredictable (some had a harder MC while others had a harder free response section, sometimes questions involved super specific syntax stuff and weird edge cases), but he re-scaled them so that the averages were low Bs (and Professor Mike gave us super cute rubber ducks to give us emotional support during exams :). I would be lying if I said I was never frustrated in this class, but ultimately I found a love for it. The professor, TAs, and LAs are ALWAYS available to answer your questions on Campuswire, and there is an amazing emphasis on mental health over grades. If you re-frame this course as a learning experience rather than just another letter on your transcript, you'll probably have some fun and definitely come out of it feeling proud of yourself!

At first, I thought his class was extremely hard. That. was before I fully realized that the homeworks are based on completion. You really get what you put into this class. If you really want to learn R, he is a great teacher. His notes are awesome, and I do think his assigned homework is useful to complete (you do have to attempt the homework, but not graded on accuracy). In my opinion, tests are not easy, but he curves a lot. He also allows around 3 pages of cheat sheets. If you have a coding background - this class is easy.

I would highly recommend this professor. Although the class is quite fast-paced as we go through a lot of R material in the space of 10 weeks, Mike was very good at explaining concepts and was very helpful. Most importantly, he was very fair with his grading scheme. As you can tell, a good chunk of the class ends up with A's as he curves each midterm and then also does a final curve at the end. As someone who has never coded before in my life, I guarantee you will get an A if you are willing to put in the effort to learn the material and complete the homeworks.