STAT 3220

Krista can be tough! She goes through all the stats theory properly and equips you well for anything graded. With that said, she can be tough and stern with expectations of the class, so make sure to follow up to her standard and you'll be fine.

#tCFF23
This class is pretty easy. Like some other STAT classes, Prof. Varanyak drops the lowest grade in almost every category so you can take the L quite a few times and still end up with an A. There's a "lab" for every unit, that's more like an extended version of the classroom and just tests your ability to actually replicate the stuff she goes over in class. The material is really useful, if a bit dry, and the lectures aren't the most engaging... but honestly Krista is doing her best with what she has. Linear regression just be like that. No exams, just a big project that's due in two chunks plus a presentation with your poster, oh and it's a group project btw. She grades very nicely, though the TAs do vary a bit in their niceness. Pretty lowkey class all in all.

EASY CLASS TO GET AN A
BUT HOLD ON FOR THE RIDE OF A TERRIBLE PROFESSOR, ESPECIALLY IF YOU NEED TO REACH HER!!!

-----> Read below to see how bad she is:
I am currently a fourth year and in all of my semesters at UVA, I have never had a worse professor than Krista. One the first day of classes she urged us not to email her as she would not be checking her emails and instead ask the TAs or ask our classmates via Piazza. I assume that the thousands of dollars spent on my education are not enough for her to even care about my questions. If that were not unprofessional enough, she wears sweatshirts and leggings to class. To make matters worse, I emailed her about a personal matter that required further attention and not a matter for the TAs or Piazza. After about a week, my Dean got involved, we finally met via Zoom and remedied the situation. However, once my situation worsened and I emailed her about it, she did not respond for a week. I then followed up and waited another 3 days before a response. Her response asked about setting up a meeting where she asked for my availability that week... despite responding within two hours on that Monday, I did not get a response until the following Tuesday. This response was a meeting later in the week that she ended up 'ghosting' me at and never showing up for our zoom call. Eventually, we met in person, where I had to defend myself for needing more time for a family member passing away rather than her compassion and understanding during these troubling times.

Inside of the classroom, she is genuinely a questionable professor at best. Having taken an engineering mathematics course prior using R and in statistics, I thankfully had a handful of background knowledge on the topic. However, she fails to discuss the meaning of the p-values, alpha thresholds, and all of the other values we get from our code. Instead, she finds it rather of extreme importance that we are able to "Knit" our documents into a pdf so it is aesthetically pleasing. This shows absolutely no knowledge of the content and rather harps on can you copy, paste, and edit code correctly from Classwork to Homework. In class, we sit in groups and strictly conduct groupwork as if we are in high school. Lecture teaches absolutely nothing other than talking to the groupmates around you and maybe her taking attendance that day.

I do not believe she is fit to be a professor at this prestigious university at all. She would however make a wonderful subpar high school teacher in a district desperate for faculty members that have a PhD in Education and not the actual topic of Statistics.

Honestly, Professor V isn't that bad of a professor. She isn't exceptional, but can explain the content decently well.
I mostly self-learned the content from her slides and occasionally looked at the textbook.
make sure you know how to use R in this class, either by learning some R beforehand (or in a previous class) or asking help from the TAs. R is heavily used for most things in this class.
There are no exams, only 4 in person labs (basically similar to the classworks) which involve R. Regression analysis is quite interesting, and isn't too difficult if you've encountered it before (linear regression, MLR, logistic, ANOVA). There are also nearly weekly quizzes which are hit or miss in difficulty, some easy, some worded confusingly. Then there's a semester-long group project which is pretty fun and worth a solid amount of your grade.
It isn't too hard to get an A-/A, although at the beginning of the semester, an A = 95 (which was reduced to a 94).

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.

I think the past reviews of Krista were rather harsh. I think she's changed the format a bit since previous years. There really wasn't a lot of homework most weeks. She uploads lecture videos that we're supposed to watch before class, and they're helpful for the in-class group activities. The lecture video slides are thorough enough that you don't even need the textbook. She spends some time at the top of every class going over the same material as the lecture video which I rarely paid attention to tbh, I'd just get started on the in-class assignment. The in-class assignments weren't difficult, and she basically provides all the SAS code you need so it's fairly straightforward. The "homeworks" were completely optional. Instead, we had weekly quizzes on Gradescope that weren't incredibly difficult either if you looked at the lecture slides. Each unit there would be a "lab" that you'd work on with a partner that was essentially a longer version of the in-class assignments. The most stressful part of the course were the two group projects. Because the day-to-day class activities were so simple, it felt harder to actually apply the concepts we were supposed to learn to the project. My advice is to not procrastinate, get a good group, and go to office hours to ask questions. Krista and her TAs were generally pretty good about answering questions. One other gripe I had with the course was that an A was a 95 which is needlessly high imo

Learned a lot of useful methods for analyzing data and building multiple linear regression or logistical regression models. The grade is mostly based on group work so it is important to pick a good one. There are lots of little deadlines and you don't want to forget about them as their is no late policy.

Krista throws a lot of information and assignments at you- prerecorded lecture videos, daily class meetings, classwork assignments, lab assignments, monthly homeworks, and project deadlines. However, most of this work is really manageable and can actually help enhance your understanding of linear regression if you try on them. The course is an easy A if you use the examples that Krista provides and apply them to your homeworks and labs while changing the numbers. The TA's also really don't know what's going on but they grade easily. The final project can be fun and accomplished pretty quickly if you pick your group wisely. The material in this class is definitely relevant to the real world, let alone a pre-requisite for almost every concentration of the stat major, so I definitely recommend taking it.

Honestly Varanyak gets a lot of unwarranted flack for this class. This class is not difficult as long as you skim the textbook and take notes on the weekly lectures (only like 30 minutes each). Yes, we don't go in-depth to the mathematical concepts - that is outside the scope of this class. You will probably get more out of this if you've already taken STAT 3120. This class advertises basic multivariate regression skills. You will learn to do that.

The grade threshold for this class is a 95, but with how easily most assignments are graded it is not a heavy lift.
The problem sets are easy and are direct applications from the classwork and lectures.

I will concede that SAS sucks, but you can literally just copy and paste code from the provided examples and refit it to your context with extremely limited/no programming knowledge.

Whew. Krista is so difficult. While I will more than likely get an A- only because her grade thresholds are ridiculous, she is so unaccommodating. She expects us to read the textbook, watch pre-lecture, go to class every day and complete classwork (graded for accuracy) have a lab and homework (so long) for every unit, and 2 projects, it is just way too much. Not to mention, she isn't very approachable, does not allow extensions, terrible communication by email, and isn't a good lecturer, and there are barely any drops. If this class isn't a requirement, take an alternative she is such a piece of work and it is not worth your stress. It is unfortunate because I took this class during online learning, so I can only imagine what it is like in person. The only good thing really is that there are no exams, and you work in groups for class work and the projects.

I personally don't like Krista that much, but this class is generally ok. You can easily get A in this class but you won't learn much about the core concepts or the coding. Krista is nice but not a very good teacher for high level classes. She poorly explains the rationales behind concepts and the codes. You will just memorize the whatever things you need to do and correspond them with the codes, while you don't understand why you do this. Another thing is that the class is not organized at all. It has the most disorganized Collab site I have ever seen. It is very confusing with her repeated labels, tedious and not accurate instructions, and redundant resources. She could make it better by keeping the "lecture day tab" and eliminating others because they don't help at all. Homework, classwork, labs and projects take up the grade, but homework problems are not designed very well. Her wording sometimes is difficult to understand (i.e. she uses multiple terms/names to represent the same thing which is confusing ), and also expect a few questions that you never learned in class to appear in HW or lab. She gave different answers to the same type of questions, so you don't clearly know what is the right (or standard) way to do it. Besides the HW, classwork, recorded lectures and stuff, you also have the self-learning SAS lessons which costs you 2 hours per week. On the good side, the classwork is helpful as an immediate practice for what you need to know. She will give answers at the end of the class, so don't miss it. Overall, this class is ok but don't choose Krista if you want some in-depth understanding of the materials. Good GPA pumper.

Horrible teacher. Krista literally sucks. She's not remotely helpful in OH. The way she presents it is so boring. The readings are bearable I suppose. She makes you use SAS, which is really confusing and somewhat hard to use. I got an A-, so I'm not complaining just bc of my grade. I would've had a more enjoyable time if I took it with someone else. Do yourself a favor and don't make the mistake I did. Everyone else here seems to agree, so that should say something.

If you love stats, then go ahead and take this class. I realized that I only thought I liked this class due to the professor in intro, not because of the content itself.

Honestly very surprised to see how negative a lot of the reviews about Krista are, as I had a great experience with her. I took this class over j term so obviously it was at a much faster pace/a little more strenuous than it would be during a normal semester. That said I think Krista did a great job. I thought her lectures and powerpoints were super easy to understand and look back at. Also think that the classworks, labs, and homeworks were completely reasonable and actually helped with learning. Krista is super nice and very approachable and I think made the class a really good experience. I would say this is one of the best stat classes I've taken at UVA and would 100% take a class with Krista again. Not sure why other people dislike her, but I think if you put in a reasonable amount of time and effort the class isn't that difficult and you actually can get a lot out of it.

Honestly this class was amazing, I know this class had such a bad rep from the earlier years, but it is much more organized now. Krista is honestly one of my favorite teachers from UVA and she was so approachable and caring to all the students. Since I took this during J-term, the class size was smaller, but it so doable and I HIGHLY recommend her since she was always available and thoughtful.

I took this fall 2020 online as a first year. DON'T let the reviews scare you into taking this class. This course is very manageable, just incredibly time consuming. I'm convinced Krista does not realize the amount of work she gives is excessive and believes this is our only class. However, that aside, it's not that bad and easy to pass with an A+ so long as you do the work.

There's a pre-recorded lecture to go along with the reading prior to each class. The pre-recorded lecture is based on her power points and technically you don't really need to read the textbook to understand the material. In the live lectures, she goes over a class example and the codes on SAS. Her coding files for each unit are actually organized and easy to sort through. There's a class check-in with each lecture that's normally content-based or asks you to do your own example. Not hard at all. You can find the answers to the content based questions in her power points or you can just ask her and she'll guide you to the answer.

There's one homework assignment with each unit (about 4 problems with each assignment) along with a lab. They're both very helpful in preparing for the other if you choose to do one before the other. For the labs, she randomly pairs you up with someone to work on it and if you and your partner both understand the codes/content, it doesn't take more than 2 hours to finish the lab. For the home work, it does take long but it can be done in a night. It's not hard at all to get above a 90/100 on each lab and homework.

My main complaints with Prof. Varanyak is that it's very obvious she's still kind of new to teaching (she graduated from grad school only a few years ago). She sends a bunch of bs emails and rarely replies to Piazza posts that are genuine questions. The TAs are the ones that reply to the Piazza posts but they give very conflicting answers most of the time so it doesn't even help. It's obvious that she's very disorganized - even in her pre-recorded lectures she somehow manages to find an error in her power point and fixes it on the spot. Sometimes she'll upload the wrong files and and re-upload the correct ones without letting anyone know. She doesn't even follow her own schedule that she set up and shared earlier with us sometimes either.

I'm glad that there aren't any exams in this class. There's two projects but they're SO time-consuming and you have to make sure you get GOOD project partners. If someone isn't doing their part, just report them right away. I was forced to do that with one of my partners. We were initially a group of three but became two since of them obviously didn't understand the material. My biggest piece of advice is to take this class with friends. It helps a lot!!!!!!!! #tCF2020

Didn't learn a ton, but this might be the first class I get an A+ in. The class is structured into 5 units which each have a lab (done in class with a partner) and a problem set. There were no exams, just 2 group projects that matched up with the course material well and if you got a good group then they were not much effort at all. You are programming in SAS which can get annoying especially since I have a CS background and SAS doesn't actually feel like coding more like just calculating. There is a SAS course that you have to complete but she walks you through all the code you need to know how to use in class so the SAS course isn't necessary to understand the material or pass the class. The structure of the class was kind of confusing since some days were mandatory and others weren't but the in-class lectures were much more helpful than the recorded lectures since she went through the code in class and the recorded lectures was just going through the slides. Most of the code you can copy and paste from her examples and change the name of the data set and it'll work. Don't be intimidated if you've never coded before. If you're a stat major, it's not bad but if you don't have to take it, I wouldn't.

Talk about a course that is much worse than it should be. Regression Analysis is actually a relatively interesting, important and easy-to-interpret topic compared to many other statistics courses. Unfortunately, Krista drags us through a crap load of repetitive busy work. The daily check-ins are obnoxious. On top of the projects, long assignments and labs, they seem like her way of forcing students to engage in her vague lectures. You can tell she doesn't have a great understanding of the content. Literally, everything takes more time than it should. Even her collab page feels like it's designed to waste time. Thanks for making multiple folders with the same title! I almost forgot to mention that she casually assigns an online SAS course that takes ~20 hours to complete. TA's are chill at least and the grading is lenient. I simply can't get past the astronomically high effort-to-knowledge ratio.

If you do not have to take this class, DO NOT take it while it is taught by Krista Varanyak. I do not think she did a good job at getting students to understand what she intended to. During class, most students get sleepy, and even though we tried our best to keep up with her, we still get lost in her vague instruction towards in-class activity and so on... The professor also responses to e-mails so slow that you could never get your questions answered on time. I know I might be a little bit emotional but I have to say this course is the worst course I have taken so far.

This class was a mess, to say the least. I am not being spiteful, as this feedback is coming from someone who will likely finish the class with a high A, possibly even an A+. Here it goes:

We are not in middle school. This class was taught as though we are a class of 6th graders who do not understand how to manage assignments or keep up with course material. Between Collab, Piazza, Gradescope, and daily email announcements, there is too much information coming at us that is completely unnecessary and draws students to start tuning everything out. Communications can and should be consolidated. Beginning with the quizzes, it seemed like they were more focused on definitions and memorization as opposed to problem-solving and critical thinking. There were 6 (!!) of them during the semester that just added a ton of stress and did not truly assess our ability to learn. We also had in-class assignments which were her way of taking attendance (15% of your final grade). These were absolutely worthless and made it so we had to come to class, even when listening to her lectures is pretty pointless. As for the problem sets, they were generally good but extremely repetitive. These can be cut down even further. My hand was sore after handwriting the first problem set, and having to write out the exact same 3-line interpretation, quite literally 30+ times. Type these out. Also, pretty much all of the answers were on Chegg, so do what you will with that info. In terms of labs, these were valuable, but need improvement in terms of execution. The main issue was that there was never enough time in class to finish the lab especially toward the beginning of the course. I would recommend removing the in-class assignments and replacing them with more time for each lab. Side note: On the lab with the football data from the eagles, there are points in the lab when you refer to 2017 data when it is from 2018 and vice versa (we looked up the team stats on google for each year to find this out). As for the projects, there are 2 and both done in a group (total of 45% of your final grade) so make sure to pick a good group. They're graded pretty easily but the second project has a "poster session" that involves a bunch of small and meaningless tasks (such as commenting on the projects of three other groups and responding to their comments) that are a waste of everyone's time.

There are also a bunch of extra credit assignments that require a lot of time for a maximum 1% boost to your final grade. Grading wise the class is fine, but the main point of this review is that this class was so poorly organized that it made me consider dropping a statistics major. If you do the work (assuming you manage to figure out what the hell is actually going on and sift through the bullshit in her emails), your grade will be fine. It will just take a lot out of you.

Let me start off by saying this course is not impossible. However, if you must take this class I urge you to pick a professor who is NOT Krista Varanyak. She is a young professor fresh out of grad school and it shows in her teaching methods. She assumes that students will know how to do things on SaS without giving any proper instruction. The format of her class is very disorganized and she is constantly changing the syllabus. In the beginning she gives you n SaS programming course to work on but it doesn't help you figure out SaS and really just becomes time-consuming. I wish I had dropped this class when I had the chance. One positive is that she doesn't give you exams, however the projects are so time-consuming and frustrating to work through that you are better off taking an exam. She makes the class much harder than it needs to be and makes you submit some form of assignment every single class, so it's not even like you could miss a class. It's too late to save myself, but I can still save those of you who haven't taken the class yet.

Previous reviews of this course made me very fearful of Krista's teaching, but she really exceeded my expectations. She tries her very best to make a sometimes dull subject interesting, and quite frankly I really like her. She is very helpful and extremely fair. Honestly, this class is really easy because Krista really wants everyone to succeed. I never read the textbook and found that I could be successful by just attending lectures. The HW sets are also very helpful, especially with regard to how to use SAS. The two exams are pretty easy because she gives you practice for them and you can use a cheat sheet. Additionally, she grades the projects very leniently. Overall, I would recommend this course to anyone with any interest in statistics/economics/business/any field that is highly quantitative/analytical because it is easy and the material taught is extremely applicable to the real world.

I could say that people who rate this course a low score because they did not put in much effort and still want an easy A. Professor Varanyak is helpful in office hours. I admit that there are 4 case studies during the semester and a final project. But the exam are open-book and she reviewed some important questions that may be shown on the exam with us. So, I say it is hard for you to not get a 90/100 higher on exams. As I knew so far, she tries to change her syllabus and make this course more interesting and less hard for students. A cutoff is 95%, but she gives extra credit for finishing course evaluation. For the Fall 2018 semester, the A is actually 93%. If you put in effort on your group case studies and write well notes for exams, you at least will get an A-. I believed most of our class was A.

Honestly some of these reviews are obviously from students who didnt show up to lecture or put in the necessary work. Not to sound like a smart-ass, but honestly the course wasn't bad at all. As a first year, I was nervous to jump into a 3000 level course my first semester, but honestly this course was so interesting that I have few regrets. I agree that the case studies (4 mini projects worth 20% of your grade) and homework (6 assignments worth 25% of your grade) could be a bit tedious, but they were graded pretty fairly-- the case studies were graded by her and were generally pretty easy to get an A on, the homeworks however took a while to be graded and seemed to be graded sort of subjectively-- probably my only critique of the course. Our first exam was open book and online, plus had 10 possible extra credit points... how people managed to not get an A honestly surprised me because the subject matter was not very difficult. In this course, you will have to get familiar with coding in SAS, something that scared me because I had little coding experience. However (contrary to what many people seem to be saying) she presented it in a relatively easy-to-follow manor, and even released her own solutions to the practice problems involving SAS so we could go over it after lecture... honestly seemed pretty nice. If you keep up with the coding as you go, it won't be hard. Honestly, if you remember proc reg you'll be fine lol. Overall, I would recommend taking this course. It introduces some really interesting regression topics and opens your eyes to the wider world of statistics.

Very meh...
Tons of annoying little case studies. Crappy final project. Scrolling through SAS code does not count as lecture just as showing us pictures of Japanese text does not teach us Japanese. Also, I don't know if she's just bad at SAS, but it seems like you need to write Harry Potter books 5-7 worth of SAS to produce the same output a few lines of R can produce.

Not a fan of Krista. She is an extremely bad lecturer and does not really care about her students or the material. She takes forever to grade HWs and assigns an unnecessary amount of work to students for no reason. Also, on our first open note exam, she took off 10% for my answer sounding too similar to the textbook. I really don't know why, how that came up to her mind. There is no structure to her grading and often very subjective. Her cutoff for A in the class is 95%. Like why? Why do you hate us so much?

Great course! Ms.V is very approachable after class or during office hours. She will try her best to answer the questions. The projects have clear guidelines and are usually associated with daily matters, which is great. Make sure to ask her opinion if any obstacles arise during data analysis. She will help you out!

Krista is one of the worst professors I've ever had in UVA. She assigns tons of unnecessary homework every week and doesn't even talk about any homework during class. Won't take another class with her ever again.

Honestly, Krista is trying. Was she an amazing professor who I'll remember shaped my career? No, absolutely not -- but she's trying. The class was incredibly structured in the sense of homeworks, mini projects, and material. The exams on the other hand. She gave us an open-note midterm (somehow I still did terribly on that) and then changed our open-note final to a huge final project. In the end, the final project ended up saving my grade but she assigned it very impulsively and I don't know if she's going to implement it next semester. She teaches straight from the textbook, and homework is also straight from the textbook so definitely have that. The homework is tiring and long, it wears your spirit down so definitely try to get a hold of a Chegg account in some way, shape, or form. Also, I would recommend taking this class with friends because when you do mini-projects/homeworks, having someone to check your numbers and analysis with is extremely helpful. There is a mini-project due for every chapter and you're assigned a group for the first like 3 or 4, and then you get to pick your group. MAKE SURE YOU PICK A GOOD GROUP. The second half of mini-projects is significantly harder than the first half and if you have a terrible group then it's going to be hard. The hype part about this class is all the extra credit Krista gives out for going to talks and writing reflections -- take full advantage of all extra credit opportunities, they saved my grade. Learning SAS was fun, and you apply it a lot but a lot of it is copying and altering bits of her code that she posts. It might have been cool to do an independent SAS project to learn more skills in SAS because I feel like we barely scratched the surface, but I liked what I did learn. Material isn't too hard either, just read the textbook.

I personally wasn't a very big fan of Krista. She wasn't that great of a lecturer and didn't seem that knowledgeable about the subject. Most of the material I ended up learning on my own time. The homeworks were very time consuming, as well as the group projects. On the plus side, she offered plenty of extra credit, and overall the grades were really good for this class. But, I think she's also restructuring the course for the next school year, so I'm not sure how that'll work out. The material in general is pretty useful, but I'd recommend taking the class with another teacher if possible.

I thought the professor was great, probably my favorite this semester. Although I probably seemed aloof in class, I appreciated her enthusiasm for the content and her "jokes" such as "My office hours are moved to Friday...not like anyone shows up anyway". Her miniprojects are actually quite fun to do and seem very practical. She started the semester asking students to tell her if they get too stressed which is also something I appreciated. She also offers to give advice about jobs, graduate school, etc. Overall, she's a professor who seems to care not only about teaching students, but also their wellbeing.