I took this class in spring 2020. It might be due to covid-19 and the protests but Professor Lew was generous with grading. She is not the best lecture but she definitely structured the class very well. Unlike professor Tsiang who also teaches Stats20, professor Lew tailored the class toward statistical consulting and the things you learn in the class can be connected to real life in a number of ways. Plus, I did not have Jake as the TA for this class!

Took this class during summer session, so the schedule is tight. I personally find her lecture too fast and lack of concentration. We have to self study most of the materials through assessment.

There were no tests, but the labs are hard. In summer session, TAs are not really connected to the course and sometimes cannot answer our project related course.

During our final project, we are required to do sentiment test using an online package, while later in the project the link to the package is completely corrupted so no one can download the package anymore, the only solution is to reach out to her personally through email, which she never replies in time. People are still struggling on the 1st question several hours before due date because of this.

After 3 days' grind, with minimum sleep and rest, I finished a logical and aesthetic project, but because of the sentiment package error I mentioned earlier, I couldn't compile my file unless on a computer with English language package, which is not at all a pre-requisite in the class, and the professor refused to provide a solution and insisted that I have to use others' computer or redo my project, this is just unfair

Note: professor lew changed the structure of the class starting this quarter. I didn't really like how the lecture was slide based and professor lew isn't the most organized lecturer lol. I wish she could've coded more during class like how cs professors do. The way this class was structured didn't really help with the projects we were given and there were a lot of self studying that needed to be done. but doable class if you try

Not sure about normal quarters, but in summer the class was kind of in hurry. Studying out of class is a must for this class in summer, but her slides are very useful in reviewing the concepts. The breakdown of this class is:

Labs (best 5 of 6): 20%
Lessons (best 5 of 6): 15%
Participation: 10%
Attendance: 5%
Lab Final: 25%
Lecture Final 25%

Labs are assigned quickly, and you are pretty much guaranteed full credits if you know the concepts well and carefully read the specs. Lessons are weekly online quiz taken in CCLE. You can attempt each quiz as many times as you want before it ends, and they only keep your highest score. Some of the lessons questions can be tricky. Prof. Lew uses CourseKey to measure attendance and participation. To receive full credits on participation, you have to use to chatroom to chat with your classmates which are kind of annoying since the design of the chatroom is not that great. The lecture final is all multiple choices and there are 29 questions. She tested many detailed syntaxes in R which are either not mentioned in class or just briefly go over in lectures. I would suggest you print out all her lecture materials for the lecture final (open book). The lab final is easier if you rigorously do all the labs. Both finals have a mean and median at around 65%.

I absolutely loved Prof. Lew's class! Lew was super passionate about teaching R and told us a lot of amazing things about how R can be applied to the real world in statistics and so on. She gave us a lot of useful tools that we could use in R and they have helped me a lot in my own programming experience in R.

She assigns homework every week and you have to use R Markdown to help you format the homework nicely. If you do it really nice with good formatting, you're bound to get full points on the homework every time. R Markdown is absolutely amazing at presenting data and charts from R and I recommend you learn all the nifty tricks that she doesn't go through much in class about markdown (because they aren't technically R coding skills).

Her lecture slides are super helpful when you need to figure out how to do certain stuff in R, and if all else fails, the R documentation is a solid go to choice to figure out how to solve the problem you want.

She has a written final which is completely open book and kind of based on her lectures so I recommend you print out her entire lecture notes and use it as reference so that you will be fine! Then she has a completely open internet practical exam on CCLE where you have to use the Stats Lab computers to do it, which was a bit annoying since I am a Windows User and the stats Lab only has Macs, but I got used to it over the 6 weeks. The practical exam really tests your hand at working data, so I highly recommend you do the homework rigorously and play around with R a little bit.

Highly recommend taking this class and this professor because they helped me a lot in life.

P.S. What I did for practice was that I webscraped data off www.dotabuff.com and used the stuff I learned in class to compile advantage and win rate matrices which then helped me to improve my drafting and counter-drafting in DOTA 2. You could probably do the same with LoL. I had to code entirely new functions on my own, using things like "apply" , cleaning up data and conditioning on variables and splitting and merging columns / rows from data frames, all of which will be super helpful in learning and using R.

As most students probably know, Lew is superb and cares a lot about student learning. I took her Stat 20 soon after it was created as a class by the department and learnt so much from her lectures. Her handouts were clear and well typed. She knew how to teach coding and how to motivate students to practice on their own. Go to her office hour whenever you have a chance, it's not optional if you're a stats major. (It's of course optional, but she's always a helpful resource regardless of your skill level.)

She and Professor Chen (also Stats department) are easily the best professors I've had at ucla so far, Lew is also one of the nicest people i've ever met (don't mean to imply that Chen is not also very nice- I just didn't interact with him on the level I did with Lew so I can't say) . One thing though is that the tests are time-compressed, but they're open note, so you just have to prepare your cheat sheet well and be able to quickly recall where certain information is located on it

She is very nice and helpful (unless she catches you cheating or being dishonest). Lectures were very clear and interesting, though the learning curve for R is steep. Attendance was taken with Top Hat Lecture, where she gives a 4 digit code at the beginning of class and you put it into the app or send it via text message, so you could hypothetically make a friend and have them give you the code when you miss a day (though don't let her catch you doing this). She does post the slides but they're not easy to follow if you didn't attend the lecture. Assignments and labs were often quite long but all of them were helpful for learning the material. Same goes for the final project. Exams were open note, but quite limited on time, so knowing the material is quite necessary.

Professor Lew is very helpful!!! She definitely cares about her students and loves teaching. Midterm and final are all held in the discussion section. Her exams are fair and manageable (open notes, open Google, open everything). Take her if you can!