I enjoyed this class although the class is not set up for everyone. It's pretty easy to get an A as long as you do the work. The majority of the grade comes from the final project. This project takes a lot of time, and it can also be frustrating if you don't have someone in your group who is good with R. However, it's pretty easy to get a good grade on it if you follow the rubric, just takes time. The hardest part of this class comes from the labs, but if you study the classwork questions beforehand, then you'll be fine. She also drops 2 quizzes, 1 lab, and gives some extra credit opportunities which really helps the grade. As a professor, I like her but I know my friends did not enjoy her. It is frustrating that during class she just reads from her notes that you can read, but she is very good at answering questions, and she is always very nice. However, I accidentally forgot to submit a classwork one time, and she refused to accept it at all, which was frustrating. All in all, not a bad class definitely recommend for stats. #tCFF23

I am very torn about this class. On one hand, if you do the work and follow instructions you are almost guaranteed an A. There are no tests and Krista has a very generous drop policy for the short quizzes. But, this class is not taught well at all. Krista does reverse classroom where she makes you watch a 30 min video before each class, and then during class you just do problems with your classmates. There's really no reason to actually go to lecture, and I stopped after the 2nd week. My bigger complain is that this class is based on the programming language SAS. SAS is a totally out of date, obscure language that is basically never used in the real world. Krista never teaches it to you, and instead tells you to go take an online tutorial and figure it out yourself. I see absolutely no reason why this class wouldn't be taught in R or Python (both significantly more popular) except that Krista doesn't know these languages and refuses to learn them. This combined with Krista's horrible email response rate along and inflexibility with meeting with students leads me to believe she is not a highly motivated professor.

TLDR; very easy A- class, don't need to go to lecture. You will learn a little about statistics and a programming language 99.9% will never use again. All things considered not a bad class, just taught in a very weird way.

Recorded videos and in person lecture were really important to my learning in this class. I would watch the recorded videos and take notes, and this was helpful because the videos had built in learning check points that I would gain even more information from. The videos also worked through some examples that were similar to what we would see in classwork. In class lecture would summarize what I learned from the videos and Professor Varanyak would then go through the code in SAS. These two activities, rather than the class textbook, were how I completed most of my learning. Labs, quizzes, and classwork assignments are the bulk of the class with a final project. For the project, you work in a group of 3-4 people and have to come up with a research question and find a data set to design a model for linear or logistic regression. Classwork and examples from the class are more than enough to prepare for this assignment, but you can go to office hours to get feedback on it while you work on it. Definitely start early with this project! #tCFfall22

I don't understand the criticism for this course and instructor. This class is almost a guaranteed A if you just do the assignments and work as it's laid out. Yes, the organization of the course was sometimes lacking, and, yes, she does grade somewhat critically without much feedback on the final project. However, I felt that she was very clear in her expectations communicated via the rubrics (and they were pretty high), and if you needed clarification as to why points were lost, she was readily available to explain during office hours. I think people just blew this class and a lot of the assignments off as easy A's and didn't take her rubrics/expectations seriously. Really no fault of hers. Granted, the whole course is pretty easy and low maintenance up until the final project, which is much more in-depth and intense than any of the other coursework. However, I think the project was a very fair demonstration of everything that we learned. That being said, it's incredibly important to choose your project group carefully as you will most likely be working with them for the better part of the semester. Some people hate SAS, but it's SO easy to use and most (basically all) of the coding can be done by directly referencing or copying and editing code that she literally gives you. Learning and actually having to write your own code in SAS is a very small fraction of the coursework.

This class doesn't involve a lot of work in my opinion and the stuff you learn is very useful and most likely applicable to your career if you're pursuing a statistics related one. There are no tests which is pretty great. However, Krista is a very harsh grader which ended up docking a lot of points for the final project. Speaking of that, make sure you pick good partners for that as it can really make or break your grade. Don't forget to do the weekly quizzes like I did a couple time because gradebook unfortunately doesn't send reminders. Also the grading scale is so dumb and makes no sense why a 93 is not an A.

Understanding the concepts of regression is absolutely crucial to statistics, and if taught well, can very effectively be used as a "bridge" to connect introductory statistics courses to higher-level "machine learning" ideas (e.g. the sigmoid function used in logistic regression is also a common neural network activation function). The idea of a hands-on regression course with plenty of practice with linear, multiple linear, and logistic regression is very sound, and when I was actually doing the coursework for this class, I found it to be extremely relevant and useful to future statistics courses I may take. The in-depth exploration of the regression assumptions in STAT 3220 stood out as one of the course highlights — understanding concepts like homo- vs heteroscedasticity & interpreting Q-Q plots is VERY handy when actually applying regression techniques in the field. I am very glad that UVA offers this class & think the overall material is incredibly valuable.

That being said... the actual experience of this class was very frustrating, for a few reasons:

1. The entire course is taught using SAS, a dinosaur of a programming language that is almost totally obsolete outside of the field of biostatistics and is a total pain to learn. It's so convoluted that the instructor required us to complete a 20-hour course on the basics of the programming language and beyond the basic proc... and data... syntax I'd be hard-pressed to pass any sort of programming exam on the language. It's inflexible, doesn't really support functional or OO programming, and has horrible documentation. I legitimately cannot imagine the justification for teaching a statistics course in SAS instead of R or Python in the year 2022, especially because SAS is not open source and charges an excessive amount of $$ for access to an online web editor (that's right, you can't even program in SAS on your actual computer, you have to use an unresponsive and buggy code editor in the browser).

2. The feedback on assignments ranges from "pretty useless" to "totally nonexistent." Points are taken off arbitrarily on labs and even MORE arbitrarily on the final project, which — despite having multiple full class days devoted to it — was never really clearly defined. Some cautions on the labs: while during the lectures and homeworks, the professor emphasizes the arbitrariness of the regression model building process and the lack of black-and-white answers in variable selection (the "garden of forking paths" is a familiar concept to students with a statistics background), do NOT deviate from whatever the graders have on their answer key — no matter how far you go to try and explain your reasoning, it won't be far enough! If you're worried you don't understand the content covered in video lectures, some copy-pasting of the HW code + changing of numbers is good enough to earn As on the labs.

Don't get me wrong, regression analysis is a crucial part of Statistics, and this course is very foundational, albeit barebones. However, it's really not as big of a deal as the Professor Varanyak makes it seem. She also doesn't really try to make this class interesting.

There's a really big ego coming off from her. She seems to think that this is the biggest class we're taking this semester, and our absolute priority. Assignment extensions? For what, other classes? Why aren't you prioritizing this one? What, you don't know SAS? Here's a 20-hour tutorial for the programming language that you'll only use for this class, because R is better in virtually every way, except maybe one or two cases. What do you mean you don't have time for a 20-hour tutorial? You only have 3 lecture hours a week.
She uses the "flipped" classroom style, giving these worthless presentations that don't advance your knowledge of the material at all. People caught onto this pretty early, and she openly complained in class that no one watches her lectures (I wonder why). She is extremely unaccommodating, and is useless in OH, basically agreeing with whatever you say, even if it's very much not right. On that note, she also complains that no one goes to her office hours (I wonder why).
There are a few diamonds in the rough, however. She posts a lot of extra practice problems (with solutions), and assignments/labs in this class often are very similar, so it's not like she completely leaves you in the dark. There is a lot of structure to this course, and she's pretty good with following the schedule she establishes at the beginning of the semester.

Let's talk grading:

Assignments: 5%. You can copy/paste SAS code, with a few numbers changed around, and you're practically guaranteed a 99%. She drones on through SAS code for 45 minutes, do the assignments during then, and you can leave early 98% of the time (she won't give you enough time to finish the assignment in class if you actually pay attention to her lectures).

Quizzes: 20%. You're guaranteed to miss at least one question on these, because these questions are hyper-specific, but since Regression is your only class of course, you should be fine, since you've obviously memorized every word she says in her VERY pointless recorded lectures (she might say the answer in these, like once. Maybe). One of these grades is to got o events related to the Statistics department

Labs: 30%. Basically a harder assignment that takes the entire class time (she won't lecture on these days). They're pretty doable if you look at the assignments.

Project: 45%. She should try out for the cheer team, the way she stretches to mark off random points on this.

Overall, get ready for a professor who acts like she's spearheading the revolution in statistical learning. This class could've been so much easier if she didn't act like this was our only class.

#tCFspring2022

(+): easy A, organized materials, approachable professor/TAs
(-): graded in-class works (=participation is required to get grade), all team based works

Take it if you want easy A
Do not take it if you don't like to go to class or prefer individual work

I really enjoyed this class! Professor Varanyak used a "flipped classroom" where she posted video lectures we had to watch before the class, then reviewed the material in the first thirty minutes of class, and we spent the rest of the time working on group work, short daily classworks based on the material we had learned. SAS was really tedious and irritating to learn, but she gave us more or less all the code we needed. We had "labs" for each unit, basically a larger classwork with material from the whole unit, which was in partners, weekly open note quizzes, and a large final project split up into two parts. To anyone considering taking this class, I say go for it, its not that bad, and focus most heavily on the quizzes, labs, and project - don't slack off. #tCFfall2021

Krista has DEFINITELY listened to reviews and has changed this class for the better. A lot of the complaints listed in reviews from previous semesters have been fixed. Homeworks are optional, there is no busywork, and the workload is extremely minimal. On average, I spent less than 1 hour working on this class outside of lectures. Instead of homework, we have 10 weekly quizzes that are a total of 15% of your grade. She drops the lowest 2, and the last 2 are automatic 100s (for completion). I thought the material was interesting and Krista was super nice and approachable. The bulk of your grade in this class will be from the project (20% for part 1 and 25% for part 2). The rubrics are straightforward, and I found it very easy to be successful in this class.