STAT 3080

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

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

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 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

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.

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.

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.

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

Martinet is not really that good a professor, but I would say it's still one of your 'easy A' classes. There are no exams, but instead a research project that you work on throughout the semester. This is supposed to be an introduction to R class but I will say I've learned a lot about the code. The code she gives you is incredibly basic, and I spent a lot of time googling more rather than looking through the scripts she gives. There is a pre-recorded lecture that goes through the code before each class. Class time is spent working on a daily assignment that is more code-focused and not really conceptual with a group. Most times they were pretty easy to get through but towards the last two scripts they were a lot harder. She loves running monte-carlo simulations. Don't worry about the daily assignments. At the end of the semester, this was the cutoff for an A with the daily assignments (which is really easy to get so long as you answer every question): "There were 399 total daily assignment points throughout the semester. The threshold for 100% is 315 points. If you earned less than 315 points, your percentage is your number of points divided by 315." The homeworks were okay - you can knock them out in a few hours, especially if you have a friend to review them with. The homeworks were where I spent more time googling the code rather than looking through what she gives because it didn't help that much. Stack overflow was a great resource for this class! No readings were required. A pretty simple and straightforward class; not much to stress on here. Just make sure you take it with a friend or two, but could be done on your own as well! #tCFspring2021

Really mixed feelings here. Pre-recorded lectures were terribly boring, simply just had to watch her code. Daily assignments were also pretty awful in my opinion. Make sure you have a good group -- mine started out with 6 people, all of whom either dropped the class or got the answers from their friends in earlier sections. I struggled with the daily assignments, but ended up getting full credit for them at the end of the semester. I would also suggest making friends for doing/checking HW. I had R experience, and they still took me a really long time. Definitely go to office hours for those, the TAs will tell you if you're right or wrong. Everyone did pretty badly on the programming quiz, I think I got an A, B, and C on them. They don't end up mattering as much as you think they will in the end, so don't stress about them. I really ended up enjoying the project, you can pick whatever dataset you find interesting and it's easy to get help from Martinet/TAs if you get stuck. You'll learn R, but probably won't have fun doing it.

This course was not particularly difficult, it was just impossible to have a clear understanding of the grading. For example, she took 10% off of my final project for something that was "missing" despite it having been explicitly included. Lectures were done asynchronously, and each one came with a daily assignment. Most daily assignments made reference to material which was difficult to find explanations for and had questions which were unclear and graded pretty strongly without any real feedback (right/wrong was all I received). Homeworks were actually the best part about the course imo; some weeks they were interesting to work on, and the feedback was more helpful for improving. The programming quizzes were not too bad, so if that's your primary concern, don't worry about it. Feedback was not given on these either, you really only got "partial credit", "less partial credit", etc as the feedback. Several "explanations" Martinet gave about things in R which were fundamentally flawed in CS terms, which is particularly irritating. A lot of the other reviews for this class say Martinet is a really great professor, so maybe I just didn't vibe with her personality or something but I absolutely could not be happier to be done with this class.

This class is pretty useful and isn't a ton of work. The homework were reasonable and didn't take a ton of time most weeks. The most annoying things were the daily assignments (I think she usually does clicker questions when the class is in person), but they just took awhile and weren't really helpful. Overall, not a bad class, if you already know R it will be super easy.

#tCF2020

The course has a clear structure, and there's a straightforward solution to doing well. I was a little intimidated at first, because this was my first time with R. And I took a while to get used to it. But once I did, this class became very easy.

The grading is largely homework (40%). We also had Daily Assignments (15%), Programming Quizzes (15%), and a Final Project (30%).

The 3 Programming Quizzes were HARD. No point in lying. I was rushed for time and a little lost on where to start for the problems, and I epically failed the first one. However, she gives a moderate curve, and the quizzes aren't worth much in the end. Lastly, the quizzes are only in the first half of the semester.

The homework is very easy if you follow her lecture script. At the end, I was literally copy/pasting the script into my homework, and changing numbers around. I had a good group (from the Daily assignments), and we would go over our solutions together. This helped, because they noticed things that I didn't, or got better answers.

Daily assignments are also group work, and follow similarly to the homework (with the copy/pasting). You get half of the points for just answering the questions, the other half is based on correctness. These are computational, but reveal the conceptual aspects of the topics, and were quite interesting.

The project wasn't even really mentioned until the last month and a half. The first section (of 3) was to look at a data set of our choosing, and was peer reviewed based on some rubric. The next part was to conduct a significance test of our choosing. It really depends on how good your data set is, so choose a good data set.

Overall, this class is very doable, if you know how to do this class. Here's my advice: 1) Get a good group, or at least be active. They can help you with the homework. 2) Review her R script. They're what you will be doing for the semester, so get familiar with it.

Unless you hate flipped classroom, I would recommend this course (especially during online learning). Before every class there is a 30 minute video to watch and then you come to class to do a daily assignment in a group of 5 that only takes about 40 minutes so you always "get out" early (the group doesn't change all semester so getting a good one helps a lot). There were no exams only 3 programming quizzes that people typically don't do great on because time is very limited but she ended up curving 2/3 quizzes. Every Wednesday (at 9am) there was a homework assignment due that took anywhere from 1-3 hours to complete. There was 1 project done in 2 parts: first part was mainly graphs and your classmates grade that one and then the second part is a statistical test which the Professor grades. Martinet was very friendly and helpful for anything we needed during class or in OH. If you need a stat elective, I would highly recommend this one!

I would definitely recommend this course with Professor Martinet! The notes are easy to follow, she's super nice and always willing to help. The programming quizzes are the hardest part of the course but tbh you don't need to do well on them to get an A-/A in the class. The majority of your grade is based on the homework assignments. There's one due every Wednesday each week. For the most part, they weren't overly difficult because the R script corresponds well. Office hours are really helpful for any homework help and would 100% recommend going to them! There is a final project but as long as you follow the rubric, they're not hard. Martinet does have clicker questions so you'd have to go to lecture. Most of the time, people would do other work in lecture since all R scripts are uploaded on collab and you can download & learn it for yourself.

This class was super chill. Honestly put in minimal effort for it and still ended up with an A. The homeworks were a bit tedious, but definitely doable. There are no exams, just programming quizzes. I tanked those and still did fine!

This is probably the best stats class I've taken so far at UVA. Prof. Martinet is great. She is super helpful on work if you go to office hours, and she is willing to answer all of your questions. Homeworks could be long, but not too difficult (especially manageable if you went to office hours). There are three handwritten programming quizzes; they are difficult but are only a small part of your grade. Project wasn't too bad. There are clicker questions and extra credit opportunities as well. The grade breakdown is: Programming quizzes 15%, Clickers 10%, Homework, 40%, Project: 35% (Part 1: 10%, Part 3: 25%).

This class is a bit of grinder but is an easy A- (A is 95%) if you're willing to put work in. Material is SUPER useful, especially in 4000 level stat classes since many use R, not python. I recommend going to OH every week to get your homework checked; they have OH four days a week at multiple times so it's really flexible! I never got below a 97% on the homework by doing this and homework accounts for 40% of your grade. Participation is 10% so you have to go to class to get clicker points but Martinet said the buffer is low enough that if you go most of the time you should get full points on that. Quizzes are 15% and a bit difficult but I wouldn't super duper worry about those to be honest if you just review a little the night before. Practicing writing the code by hand helped me prep for the quizzes than just squarely looking at the R script. The project is 35% but if you follow the rubric then you shouldn't have an issues whatsoever. Definitely would recommend if you need a Stat elective. Martinet is super nice and understanding! Of course class is boring but it's nothing a little coffee and work for another class can't solve : )

Incredibly useful class, and the R is really practical. Grading is consisted of weekly homework that are relatively straightforward, and office hours can be helpful if you have questions. Martinet is a great professor that really cares about her students. There are also a few programming quizzes at the beginning of the semester to test your knowledge and make sure you can do the coding required. The material at that point is pretty easy so just take some time and review the notes beforehand and you should be fine.

There is also a final project that is a really cool application of what you learned. I loved how this class was structured (I wish all the statistics classes were structured this way) - teaching practical experience to students is so helpful in real world applications (I used my skills in future jobs/internships)

This is a grinder, but deceptively easy grading. Martinet does a good job with a relatively dry course.

Grading is 35% project, 10% clickers, 15% quizzes, and the rest homeworks (as best I remember).
Project is split into 10% for a proposal, and 25% for a final submittal. Both are clearly laid out on rubrics, just make sure to find good data ahead of time.
Clickers are not very difficult, and there are enough that everyone should reach the buffer point.
The programming quizzes are so hard. Paper coding is rough for anyone, much less a non-CS major. So much code is covered each class that without a lot of study the quizzes can tank you. That said I got an A with about a 66 quiz average so not all is lost, but put in a good few hours prepping for these.
The homeworks are, well, a pain in the ass. They are very helpful to learn the material, and tend to be pretty straightforward. However, as the semester goes on the coding becomes much harder, and there are often "leaps of thinking" needed to get a good score. There are TA office hours, but queues are long. Be sure to make a few friends to bounce code off of, otherwise you will spend hours a week in a stuffy room waiting for TA help.

Learning Monte Carlo simulation is cool, and it is a good intro class. It seems stressful as the year goes on, but honestly wasn't too bad.

If you are worried about a lack of coding experience coming into the course like I was, don't be. The course is not as intensive as a CS course, and you should be able to pick up on a lot of the coding fairly quickly as long as you have at least some experience with it. While I didn't think Martinet was the most engaging professor I have ever had, she is very caring and always willing to help out. The only thing to be concerned about as far as the coding aspect is the quizzes, which there are only 3 of. Since there are only 3 and they're collectively worth 15% of the grade, if you're a little shaky on the methods, I highly recommend going back and re-doing the homeworks beforehand to get some practice. Overall, a fairly easy and worthwhile course if you're looking to get credit for the STAT major/minor.

This course is great for people who are interested in learning the basics of R and new statistical methods. The class is minimal work, with just weekly homework assignments, 2 of which can be skipped/dropped. Prof. Martinet is awesome and I genuinely looked forward to coming to class each day because of her. Other assignments are in-class quizzes which can be tough, but are doable if you study, as well as a project which is actually kind of fun because you get to choose your own data set to explore. Overall, a fun, pretty easy and enjoyable course.

Easy enough class if you have basic programming experience. Assignments get a little confusing at times, so just go to office hours and they pretty much walk you through it. Had to go to lectures because of clicker questions, but they weren't too bad. I think we had like 3 quizzes throughout the year, testing on basic programming knowledge and syntax. Study for those and you'll be fine. Also you get two homework drops, which is pretty clutch just in case you forget to submit an assignment.

Great Professor! Class was super easy to get an A in. Class contains mostly of programming assignments (which you can drop your lowest 2) and you just have to go to office hours if you need help. There are programming quizzes (3) but those are doable. She does require inclass participation through iclickers, but she is open for you going to other lecture times. overall great class!

I generally agree with the other reviews. I'm a CS major and found this class to be very easy, mostly because 1) R isn't a hard language to pick up if you already have programming experience and 2) Only basic programming concepts were covered. If you're worried about going in with no prior programming experience, I'd recommend going through a basic R tutorial on Datacamp a week or so before the semester starts, as that will provide a short overview of what you can expect in this class.

If you have prior programming experience, then this class will pretty much be a breeze. I didn’t have any background in coding coming into the class and it still wasn’t too challenging as long as you’re willing to spend some time reviewing her notes and googling. The final grade consists of the weekly homeworks, 3 programming quizzes, clicker Q’s, and the 3-part final project. The homeworks and the quizzes are by far the most difficult components of the class. The homework can take upwards of 5-6 hours to finish if they’re difficult but reviewing with a group helps a lot. The quizzes were really hard for me due to my lack of programming knowledge but you can scrape by if you dedicate a fairly sizable amount of time to studying each notes section. Professor Martinent is very lenient with the clicker questions so you can miss a bunch and still pull a 100 for the final clicker grade. The project may seem a little intimidating but the rubric she gives you is very straightforward and simple so if you follow that, you’re guaranteed to do well. Overall, I enjoyed the class and if you’re looking for a statistics elective or introduction to R that won’t kill your GPA, this is a good option!

I personally hated this class for a variety of reasons but 1.) R is a useful and cool language and 2.) There aren't that many statistics electives, so I would say this class is a take

I have pretty mixed feelings about this course but overall it wasn't that bad. Professor Martinet is smart and a pretty solid lecturer. She is also mostly fair. My favorite thing about this course was simply learning R, as it is a very cool/enjoyable programming language to learn. With that being said, I think there is a lot of potential to make this class better. We rarely got a chance to actually analyze real data online (with the exception of the final project) and I think that doing this more would have made the class way more worthwhile. Most of the time, the homework assignments felt random and not applicable to real life at all. One very nice thing about the course, though, is that there are zero midterms and no final exams. If you are willing to put in a solid amount of work on the homeworks, then I would mostly recommend this course.