STAT 3080

This class was very manageable. The daily assignments ended up being evaluated very leniently (you only needed 78.9% of the total points), but I would still strongly recommend taking the class with a friend or finding another classmate to talk them over with because the group you're supposed to work on them with (I had a group of 6) may not be very reliable. The homework was usually doable in a single afternoon or evening, but talking it over with a friend and asking questions in office hours helped me catch a lot of mistakes and was extremely helpful overall. There were three programming quizzes towards the beginning of the semester which I think a lot of people struggled with. They only make up 15% of the grade, but I was able to do well on the second and third quiz by spending more time going through the lecture scripts and practice script, and it is possible to do well if you put in the effort (as are most things). The semester long project makes up 40% of the grade, but I do not think it is difficult to do well on it if you go to office hours to talk over what you've done and any questions you might have.
However, I do feel like it is relatively easy get a good grade while not learning very much, so that is probably something to keep in mind if you want to continue studying statistics in the future.
#tCFspring2021

This course is extremely useful and if you stay on top of your work it will not be too overwhelming. However, if you are interested in feeling supported by your professor, I would not recommend taking it with Professor Martinet. She will not respond to emails that she doesn't find relevant and is not especially willing to ever discuss grades. Taking this class virtually was frustrating, but it might be a much better experience in person.

The class was fine, but the way the major project is done through Peerceptiv is pretty awful. Basically, you submit your work, your peers review it, and then your grade is based on your peers' grades of your work and the closeness of your own reviews of others to the average rating for their work. It's very easy to get a far less than ideal grade, even on the proposal. I got an 80 on my proposal because my classmates decided I didn't define the data I would need specifically enough, even though we weren't supposed to look for data during part 1. It was very frustrating to have followed the instructions and then get punished for it anyway because my peers didn't. Overall, this class is pretty good, but the project is badly executed.

Do not recommend for non-stats majors. I really struggled with the assignments, and had to go to OH every week for them because the lectures did not include everything you needed to know. This class took more of my time than any major class.

This class is honestly pretty difficult if you don't know that much STAT. Professor Martinet is very nice and a great professor. She does her best to help you understand the course concepts. The class itself is set up as a flipped classroom: you watch pre-recorded lectures by Professor Martinet and then do in-class activities during lecture that relate back to the lecture. Honestly, some of the in-class activities are more difficult than the examples shown in the lecture, so if you don't have a STAT background, keep that in mind. Introduction to Statistics is a pre-requisite, and I agree that you truly do need to remember/understand what was taught in that class to do pretty well. There are weekly homeworks, which are pretty manageable so long as your start early. The coding quizzes are probably the hardest part of the course, so make sure you're paying attention while you learn R. Another major part of the class is a project, which is pretty easy and lets you figure out how to apply course concepts to something you're actually interested in. All in all, the class is pretty interesting, but it's a bit difficult if you're not that good at STAT. #tCFFall2021

A pretty solid class overall that I would recommend for stats majors looking for an elective. The class is set up as a flipped classroom, so you watch lectures and then come to class and work on short problem sets until you and your group are done. Getting a solid group is important, so I would highly recommend taking this class with a friend or two if you can. You also have weekly homework that can be pretty tricky, but going to office hours is super helpful, so if you start early and feel free to ask questions they aren't bad at all. The main aspect of the class grade wise is a semester-long project, but if you pick a topic that you know you can find data for and use a hypothesis test on it isn't stressful, as you don't really have to do too much for it at all. Martinet is really helpful in class and in office hours, and she obviously wants you to succeed, so going to her is always a great resource. Overall a class that taught me a lot about coding and was decently enjoyable as well.

This class is essentially a CS course taught through the statistics department. Your grade is made up of 15% daily assignments, 30% homeworks, 15% programming quizzes (watch out for those), and 40% a semester-long individual project. You definitely learn A LOT of R, but you have to be really good at it in order to do well in the homeworks and quizzes as the TAs are very strict when grading assignments. This course is set up as a flipped classroom, meaning that all lectures are pre-recorded and posted on Microsoft Teams and you have to watch them before attending lecture. These lectures are basically Prof. Martinet going over a lot of R code, and you have to make sure to pay close attention as being able to code using her scripts is crucial in order to do well in the course. Classworks are the easiest part of the course: You're given the lecture time to finish them, and most of the time it's possible to finish them within that time window (you're also allowed to work in a group, which makes things easy). The project is long, but it's divided into 3 parts and shouldn't be too challenging if you pick a topic you're genuinely interested in and if you've taken another statistics course at UVA. The worst part are the coding quizzes, which require you be be extremely precise with your R code and ensure that you're paying very close attention to detail (again, the TAs are very harsh on grading). Overall, solid course, but make sure to put in a decent amount of effort and focus on the coding quizzes. Highly recommed it for people who are good with coding and like to work collaboratively with others. #tCFfall22

This class is a really great elective for stat and even cs majors. I have background in R from stat 2120 at uva, but it's definitely not necessary to do well in this class as Martinet's lectures start from the very easy stuff and builds up over time until you're fully comfortable with R. There are 3 programming quizzes to make sure you understand R (all towards the beginning of the semester) and they can be tricky but not insanely difficult. In the end, it's okay if you don't do well on them becuase they are only 20% of the grade altogether. There is a weekly homework done in R that is usually tricky, but I personally would go to the TA office hours every week to work on them and had no trouble getting them done in time (also 3 lowest ones are dropped). There is a daily assignment every day that class meets and if you have a good group and ask Martinet questions you will get full/close to full credit easily. The last big part of the grade is a final project with two parts and it's very straightforward- you just have to start early (seriously). All in all I highly recommend this class! #tCFFall23