I disagree with two of the short reviews. If you're going to take this class, Taylor is a good professor to take it with. I had him for STAT 3120 a few semesters ago as well as this class and he's by far the best lecturer I've experienced in the STAT department. He explains the concepts well and the questions you receive on the homeworks and exams are directly related to what is covered in lectures. That being said, this class is not for the faint of heart. Time series requires you to think hard. You probably won't be able to half ass lectures and homeworks and expect to do well. You'll have to focus on the prerecorded lecture videos, make sure you understand it, and try your best on the homework. If you do, you probably won't have too much of a headache on the exams. In my opinion, the exams felt like easier homework assignments, so it's important to make sure you understand the homework solutions that are posted. Overall, it's no doubt a hard class, but I would ignore the review from September 22 - that was three weeks into the semester and before we even took our first exam... #tCF2020

Grading: In-class quizzes: 10%, Homeworks: 25%, Midterm 1: 15%, Midterm 2: 15%, Final Exam: 35%. In-class quizzes are basically free points, they are pretty easy and follow directly from lecture material. Homeworks can be a bit tricky, but nothing more difficult than other more theoretical stats classes. Midterms are fair (I believe averages were low 80s). I just finished the final and found it pretty easy as well minus one proof problem (but this is to be expected for any proof-based course). Professor: I found Taylor Brown an excellent lecturer. It is true that during lecture sometimes concepts are covered too quickly or without necessary intuition, but he is responsive to emails and piazza and will explain things well in office hours if you show up. He is rather young which definitely makes him more relatable in class which I think is a plus. We had a cheating scandal on our final exam where someone posted answers on Chegg-- again, he is certainly privy to these resources (including github, stack exchange, ect) so I would not recommend trying to cheat in this class (not that you ever should but besides the point). Gradescope is used in this class for basically everything. He uses an autograder which is nice to check some of your work, but can be annoying as any typos/ bugs will render all your code useless-- not that big of a deal though. Material: Time series is definitely a difficult class, probably one of the hardest in the statistics major. The course is a good halfway point between purely theoretical proofs and applications with R. I wouldn't say R is a necessary prerec, but honestly it helps a lot-- at this point though if you're taking a 5000 level statistics class, I would be surprised if you are unfamiliar with R. None of the coding is particularly difficult, but sometimes you just need to know a few extra functions in order to get your code to pass. The theoretical concepts can appear to sometimes all blend together, but if you write down everything he says (just the lecture slides are not enough!) you'll be straight. The applications in R also key you in to what are the important concepts to pay attention to. The textbook isn't necessary imo, but it can help supplement concepts if you get confused so I would say it's worth the purchase. Overall, this isn't a GPA killer by any means. I will likely end with an A or A- and didn't put an large amount of work in-- just took good notes, did the homework and paid attention in lecture. #tCF2020

If you have to take this course, take it with other professors. The content is worth learning but the professor is bad.

Don't take this course with him.