STAT 3280 was probably the easiest class I’ve taken at UVA. It requires very little work outside of one short homework assignment each week. You’re only required to attend one class per week, and class often ends early. The material is also actually useful for a lot of jobs making it a worthwhile elective to take.

Professor Ross is really nice and willing to help if you ask questions in class or during office hours. The ICAs are basically guaranteed 100s if you just show up.

I think people really overhype how hard the class project is. The rubric is definitely ambiguous, but honestly that also works in your favor because grading can be pretty lenient. Since Ross grades the project himself, if you go to office hours once or twice, show him your progress, and make the changes he suggests, you’ll probably do very well on it. That being said even with the allowance of some AI on the project I would still plan to spend at least 10+ hours on it minimum.

Besides that, the only real downside is that one or two of the homework assignments were unusually hard, and the lack of strict instructions or a detailed rubric definitely hurt there. In summary I would say that Prof Ross is a nice guy who clearly created this curriculum to allow everyone to get an A even if the grading system and rubrics are not the best.

This review is going to be a little bit of a rant due to the class structure and professor Ross' grading/teaching style, but I think this is an extraordinary class in terms of the skills you learn to prepare you for future career endeavors. Also, just because the GPA for this class is high and it looks like an easy A, the path to get that A can be frustrating and seem ridiculous at times.

Professor Ross seems like a genuinely great person, but using the his 'specs' grading system doesn't work for this class because of its arbitrary nature and the lack of grading effort put in by him/TAs. I understand his sentiment that assignments being good enough or not is more similar to any real-world situation that you might be presented with in a job, but this is a college course, not a job. A grading system doesn't feel right if theres a chance it leaves you with ~week to make changes to your project (in the middle of all your other finals), which could dictate if you get a C or A in the class, and all of the grading specs are mostly arbitrary that he could realistically pass/fail you on any of them if he wanted to.

A simple counter-point to the late semester scrambling that the project can leave you is to start it earlier. Professor Ross understands this and encourages you to start the project early by including homework assignments in mid-march to help you get on track with the project. HOWEVER, he never even provided feedback on these homeworks, so submitting the project was literally a shot in the dark with very little guidance on how you might do in his arbitrary grading system.

I believe the specs grading system is fundamentally flawed because it encourages students to do 'just enough.' Yeah, this might be sufficient in many jobs in order to not get fired, but are those really the values that should be promoted? Maybe there should be a system that rewards you for going above-and-beyond and submitting work that clearly surpasses the standards, and other grades that are appropriate for those who are happy passing. Oh wait, that gets you really close to the long-standing letter grade 0-100 scale. There's a reason its been the same forever, it works.

Apart from my ranting about specs grading, I think this class is worth it to take because it does force you to learn some really valuable data visualization skills. However, I think this class would be so much better if it was taught by a more engaging and interactive professor. Ross told us at the end of the semester he has been working on his own data visualization projects with other companies, and it really shows because it does not feel like he puts much time into this class at all. Once a week you will get a typical, boring, read-off-the-slides lecture. The other class of the week is an in-class activity, which can be interesting, but is just another do-the-minimum assignment in order to meet his specs.

Syllabus: This course is specifications grading based. To get an A, you need a satisfactory score on 13/15 ICAs (In-class Activities), 9/10 HWs, 2/2 on the Plot Contests, and a 2/2 on the Final Project.

Overview: This class is really an odd one because I think the content is probably some of the most useful that I have learned at UVA, but I also strongly dislike the grading system that is used by Ross. It is a very useful class because you get to create numerous data visualizations and learn how to clean data in order to create these graphics. Your candidacy will be bolstered for any job that requires the use of R or the creation of graphics using data. However, for the grading, I found the specifications system to be very frustrating due to the fact that instructions could be confusing which may prevent you from earning a point. You are given two tokens that can be used to resubmit assignments. You can use one to resubmit a HW or ICA, or two to resubmit the project (or submit it late). There are two bonus opportunities to earn two more tokens.

HWs can take a few hours to complete or 30-min. This is another thing that annoyed me because there is a ton of variability in assignment length. This is the same thing with ICAs, which are basically HW assignments that you complete with a group in class. ICAs need to be completed in the class period and submitted at the end of class. Some take a lot of time and can be quite stressful due to the time constraints.

The plot contests are not extremely difficult and it is very feasible to score a 1 on both. One involves creating the worst plot possible for a dataset and the other involves using your project data to make a set of strong visualizations.

For the project, START EARLIER THAN YOU THINK. I left the work for my project until the final two weeks of the semester, and I still felt crammed for time. The project allows you to make a really cool story from your dataset, but it requires a strong attention to detail and a good bit of coding to create the visualizations needed. Additionally, you need to write multiple pages of description and explanation that goes over the choices you made in the project and the story of your data.

To summarize, I think you should take this course, but prepare for some frustration if you take it with Ross. Him and some other professors in the department seem to be really gung-ho on this specifications grading system. I find it to be a huge pain to deal with, but I ended up finishing with an A, so it definitely is achievable to do well in the course.

Professor Ross highkey makes your life a bit hellish in taking the course. He has 3 day MWF class sessions as opposed to the typical department 2 day/week MW schedule. He spends the 3rd day doing in-class assignments, which are fine within themselves, but class can feel dragged out in some aspects for this extra class within the week. That said, Prof Ross assigns homework in ways that demand a level of excellence to pass his specifications grading. At the end, you become a fantastic data visualizer. That said, you will be stressed in parts of the semester trying to get enough "S" marks for a satisfactory grade as you only have so many make-up tokens and homeworks are spaced out enough that you don't always know where your grade stands. Make sure you do everything early so you're not at the mercy of his busy schedule (as everyone else is) when figuring out questions to pulse check if you might want to revise your work. Also, do your final project as early as you can for the same reasons. Then you'll be cruising for the class.

Keep in mind that Prof Ross is harsh on the students so that they do well. When it really counts (i.e., grading the final project), he's a fair man. However, he might not feel that way throughout the course and grading ICA's (Friday In-class Assignments) or other homeworks. This is simply how he is as a professor in an effort to push students to do well and not bs the class. For that reason, some students don't like him. At the end of the day, I've grown to appreciate professors like him as he's one of the litmus tests for good and lazy students. Also really got to know him as he was my capstone prof and he's quite chill.

This class is very manageable to do well in, but it does have a couple downsides.

Pros:
- Content is quite straightforward if you have prior experience with R, and it's some of the most readily applicable stuff you will learn
- No exams at all and doable workload (weekly homework, weekly in-class activity, occasional mini-projects, and a final project)
- Specifications grading = you either get a 0 or a 100 on assignments, depending on if you pass the "specs" for each assignment, and final grades are based on how many assignments you pass specs on
- You get 2 tokens to re-do assignments if you don't pass specs and/or late submissions (there are opportunities to gain 1-2 more tokens throughout the semester)
- Dr. Ross makes himself pretty available for students to seek help and ask questions

Cons:
- The guidelines for what passing specs will look like are often pretty vague, so you may need to clarify some things before submitting
- The in-class activities often took more than the 50 minute class period for a lot of people and Dr. Ross did nothing to accommodate that, which was kinda annoying
- Dr. Ross often posts homework late without adjusting the deadline. Thankfully, most of them don't take awfully long to complete, but it's nice to be able to get it done early.

Make sure to start the project early, because it will kick your butt if you wait till the last minute. You are allowed to use ChatGPT or any generative AI tool to help you with the project, so make use of that! Otherwise, the class is fairly chill and the professor is pretty helpful.

I cannot recommend this class enough. Professor Ross cares so much about his students and I genuinely believe that the material taught in this class is some of the most instantly applicable content at UVA. There is no coding requirement to take this class but I knew a few people who came into it with no knowledge of R and struggled a lot. I would recommend taking an intro class or at least having a background in Python or some other language because the assignments definitely assume a base level of understanding. Specs grading is very reasonable and Prof. Ross gives you opportunities to earn more "tokens" that allow you to redo assignments you didn't meet specifications on.

You need to go class every Friday because there are weekly in class assignments that are required. If you make sure to put in the effort of attending and paying attention in class on Monday and Wednesday, these ICAs are pretty easy. There is homework almost every single week that takes 1-2 hours. Sometimes it's coding, other times it's reading and a reflection. You can use AI sources for everything in this class (ChatGPT is good for simpler assignments, ClaudeAI is good for more complex code). Make sure to start your final project a month in advance. For me, finding and cleaning my data and creating the first two visualizations took the longest. Because I started earlier, I was able to go to office hours before they got super busy and get my questions answered.

ICAs, homework, and plot projects are graded as 1 (pass specs) or 0 (does not meet specs). The final project is graded as a 2, 1, or 0. To get an A, you need to pass 13/15 ICAs, 9/10 Homeworks, 2/2 plot projects, and get a 2 on the final project. If you meet everything else but get a 1 on the final project, you will end up with a B. There is no + grading (i.e. no A+, B+, etc) but there is - grading if you are 1 item short (i.e. if you pass specs on 12/15 ICAs instead of 13/15 but pass enough homeworks, the plots, and the final project, you'll get an A-). At the beginning of the semester, you get 2 tokens that allow you to redo assignments. Redoing a homework or ICA costs 1 token while redoing a plot project or the final project costs 2 tokens. You can earn up to 2 more tokens by doing additional assignments. I didn't do any of the bonus assignments and used 1 token and ended the semester with an A. This is probably one of the easiest and most enjoyable classes for the stat major/minor. #tCFS25

I really liked this course overall, but there were a few things about it (really one big thing) that annoyed me and generally make me hesitate to fully recommend this course. I learned a lot about what goes into effective graphs and how to use R and R-adjacent tools to create them, which will definitely be very useful in the professional world. The coursework itself was generally not that difficult - there is, on average, one homework and one classwork assignment per week, with an occasional extra assignment or mini-project thrown in. There's also a final dashboard-type project, which you do NOT want to procrastinate on, as others have mentioned.

My only major gripe with this course is the grading system - Professor Ross uses "specifications grading", which in theory means that an assignment either gets a 1 or a 0 depending on whether said assignment passes "specs". In practice this basically means "A or nothing" for every single assignment, with the "specs" in question being very vague and subjective. Graphs and charts aren't an exact science, which makes it hard to determine what "passing" actually looks like in practice unless you attend office hours consistently. I think most people end up doing pretty well in this course regardless, but it was a bit frustrating trying to get my redo tokens and everything to work out along the way, which could have been avoided if a regular percentage grading system were used.

The actual course content was interesting and quite useful. I had never thought about data visualization in the manner presented throughout this course with various principles. The HW assignments were mostly useful in reinforcing knowledge about different data visualization principles and tools. The project was also thorough. There were 10 HWs, 15 in class assignments, 2 plot activities, and the final project (with 2 extra credit tokens), but the class was graded on specs grading (either you passed specs on an assignment or not). Here is where the course wasn't so good: the vagueness of passing specs on assignments WAS HUGE. I spent hours trying to figure out what would pass specs, only to email Ross and find out that I still hadn't passed specs yet. If the assignments were extremely clear on what would pass specs, then the assignments are actually enjoyable and pretty easy overall.
Note: DO NOT try and complete the project in a weekend, it takes 12+ hours (although you are allowed to use GenAI to help)

The actual course content was interesting and quite useful. I had never thought about data visualization in the manner presented throughout this course with various principles. The HW assignments were mostly useful in reinforcing knowledge about different data visualization principles and tools. The project was also thorough. There were 10 HWs, 15 in class assignments, 2 plot activities, and the final project (with 2 extra credit tokens), but the class was graded on specs grading (either you passed specs on an assignment or not). Here is where the course wasn't so good: the vagueness of passing specs on assignments WAS HUGE. I spent hours trying to figure out what would pass specs, only to email Ross and find out that I still hadn't passed specs yet. If the assignments were extremely clear on what would pass specs, then the assignments are actually enjoyable and pretty easy overall.
Note: DO NOT try and complete the project in a weekend, it takes 12+ hours (although you are allowed to use GenAI to help)

I'll start by saying Ross is a good person and cares about the students.

Ross is also generally clueless when it comes to teaching and is extremely inconsistent. Assignments were unclear and often tedious. There is a project due at the end of the semester, I would recommend starting this earlier than you think. It takes a good 20-30 hours to complete, and more if Ross decided you did not meet his specs (which were ambiguous to begin with). Not the hardest class but wouldn't recommend taking it with Ross.