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.

Mike is an amazing professor who really cares about your learning and mental/physical health, so don't stress too much about grades, as he curves. You still need to put in the work to do well, as homeworks are long and challenging. You can always ask for help on Campuswire and Mike or his TA will respond fairly quickly. Other than that, he is an engaging lecturer and a great person overall.

This class is an intro to R but it did not feel like that after the first week. I felt like I should've showed up with coding experience even though it wasn't required. Grading scheme is made up of homework (15%), discussions (3%), quizzes (10%), midterms (20% each), Campuswire participation (2%) and a final (30%). The homework is graded on completion. Discussions got full credit even if you turned in a blank document. Quizzes were very easy if you read the notes. The midterms and the final were very difficult.

Many of the answers to the tests were based on knowing which tiny changes to code would change the output. The tests were handwritten and heavily weighted on the free response (writing your own code). A lot of what is on the tests is not explicitly taught in the course so doing well on the exams meant that you had to spend a LOT of time playing around in R and noting the intricacies of the program. Homework had easy, intermediate, and challenge questions. Again, to solve these, sometimes you just had to experiment a lot in R.

The concepts were challenging, I wanted to cry for much of the term, and I completely expected to get a lower grade. Overall, not a fun experience. Stats 20 will make you question your intelligence. Greatest part of the class is professor Tsiang's exam curves. If you want to do well, study the notes, ask the experienced students for help, and copy down niche outputs.

Instead of trying to help you out, Tsiang takes the approach of making you feel stupid until youre computer gets fried because of the tears seeping through your keyboard

He taught the material really well and I definitely feel like I improved in coding in R. But it is difficult with the Homeworks being very long meaning that you have to work ahead on them on the weekends a lot of the time. He curves the tests very generously so you don't have to worry about those. Homeworks are graded on effort/completion, so your grade in the class will be good if you put in a decent effort into learning the material.

Be careful if you have any prior programming experience. He grades you down a lot if you use any functions we haven't learned yet on any homework or exam. We don't learn flow control until the second half of the course so if you have programming experience it can be annoying to avoid using them.

Though I learned a lot in this class, I really did not enjoy it. Here's my summary of this class:
• R is a really slow and not commonly-used language. If you're interested in data science, learn Python and take classes in the CS department instead.
• Professor Tsiang is a nice, helpful professor, but he has some strange disdain for his students that I was never able to quite pinpoint. He strikes me as a professor that loved being a college student and became a professor because that was the closest thing to it.
• The professor really prioritizes student mental health and well-being, which is tremendously refreshing.
• This class is more graded on effort than correctness, so it is relatively easy to get a good grade as long as you try on the assignment and study for the exams.
• His lecture notes are the most wonderful thing to ever be created. They are clean, organized, extremely thorough, and I'd even say sexy. ;)

For some reason, I never clicked with this professor. I tried many times to try and connect with him in class, yet our conversations were always somehow awkward and ended on a weird note. The professor strikes me as someone who really enjoyed being a college student and became a professor because it was the closest thing to it. I feel like he had some sort of disdain for me and something about him always through me off, though I’m not sure what.

However, I felt that the professor was very concerned for his students and always put in an effort to help us learn and master R. He always prioritized our mental health, which I really appreciated. The focus on putting our health and relationships before our academics was very refreshing and something I really appreciated throughout the quarter.

In terms of the structure of the class, I thought that it could’ve been better. I hated R during the first half of the quarter because it seemed very inefficient, slow, and useless. Only toward the end when we started to import data files and make pretty graphs did I see the usefulness of R. It would’ve been nice to see that at the beginning of the quarter so that I would’ve had more motivation to suffer through in the beginning. He also gave really cryptic answers to my questions about the homework, which I did not appreciate. Also, the professor is really picky about using the Tidyverse style guide, which I really hated. THE CURLY BRACES SHOULD GO ON THE NEXT LINE!

I absolutely loved his lecture notes, they were extremely thorough, well put-together, and concise. I stopped going to lecture because he would simply read off the lecture notes and code some things, so there was no point in me going in person. I thought the BruinLearn was chaotic and very disorganized, I always had trouble finding what I needed to there. Materials just seemed to be dumped online, without regard to organizing them in any logical way. How ironic!

Prof. states multiple times to let him worry about your grade and you just worry about learning. At first, I was apprehensive but by the end, you should believe him. If you are worried about grades do not worry he curves his midterms and final very generously. Super organized class with clear lectures and clearer notes (his notes even have a table of contents). I really felt like I learned a lot and was never stressed about my grade. If you need to take Stats20 take it with Prof. Tsiang.

this class is nice, and the professor is wonderful. i'm not sure how the class was before when most bad reviews were but my ta was amazing. homework is graded on effort, tests and overall grades are curved up (around half the people get an a/a- when averages on midterms and exams are around 80). this class is amazing. i think some people might find it hard if they never coded before but the class is not daunting at all imo, we use campuswire so just post ur question there anonymously. get a study group or have contact of a friend if u get stuck on homework. all homeworks automatically have a 24hr extension so thats really nice. for an intro coding class, its really nice imo (cough cough cs 31). the class isnt an easy a and you'll have to study, but this class didn't give me a lot of stress and i hope most classes are this caring.

Disclaimer—I took this class over the summer and online, which made the scheduling very wonky so my experiences as described below may not be indicative of a typical in-person session of this class.

Overall, this was a very good introductory programming class. No prior programming knowledge is assumed, and Dr. Mike (don't call him Professor Tsiang!) designs it such that prior knowledge of R won't even help you very much. In particular you are prohibited from using functions or structures that he hasn't yet talked about in lecture, which to me has some teaching benefits but also some drawbacks, as at times I and other students were unsure or had trouble remembering what we were and weren't allowed to use. Dr. Mike lectures in a way such that you won't just memorize a bunch of names but actively understand the theory and reasoning behind functions and structures, and his exams reflect this as they contain theoretical questions in addition to the traditional writing and debugging of code.

There were no live lectures save the introductory one on the first day. This also had major benefits and drawbacks. It was nice to be able to rewind and pause when needed, but a major downside was that it was impossible to space out all the lectures so each scheduled day would have 110 minutes' worth of content. This resulted in some days having insanely short lectures while others would far surpass two hours. Likewise, the length of the weekly homeworks tended to vary significantly, and the busiest week overall (in my opinion) was the week of the midterm. However, I wouldn't blame this on poor scheduling by Dr. Mike, I think it was merely an unfortunate consequence of the weird summer schedule.

Your grade consists of one midterm (two hours), the final (three hours), a final project, weekly homework (graded on satisfactory completion), and participation on Campuswire. Dr. Mike actually canceled the final project for us since the last two weeks were somewhat crammed, especially with the Labor Day holiday. Don't be afraid to ask him for extra accommodation if you need it, he is a very understanding professor and will try to work out a solution for you.

The course difficulty has been toned down. HWs are difficult to complete and require you to think outside the box, but graded on completion so you will be fine if you put in a solid effort. Attendance at lectures is not mandatory (they are posted online), but discussion sections are. The tests are difficult, but partial credit is given and they are also curved. Mike is by far the most responsive and approachable professor I've taken a class with; he wants you to succeed.