Ronald Neath

Homework in R (Not weekly- Due about every 3rd class, but again, soft deadlines, especially if he felt the class was struggling on particular concepts. We only actually got through 7 of them, and 8 was posted but not graded over reading week.) Midterm 1: Half T/F, Half short answer problems. No direct coding problems (almost entirely conceptual with a few minor computations in short answer). Average around 85. Midterm 2: This one was all short answer/ short computations. I think average was still around 85. Final: A LOT of T/F ( around 75%) and only 2 short answer. If you've done every HW yourself and read the book well, you should understand the concepts enough to do fine on T/F.

I was skeptical of Ronald at the beginning but I grew to like him. Don't be thrown off if you do poorly on the first homework (he says he's a tough grader) but once you get used to his style and the sort of details you need to include, it's doable to get almost full credit on every homework after that. I've HATED every stats prof I had before this (1211, 3105,3107) and I finally started to appreciate Ronald as a breath of fresh air (Tests that actually reflect the homework we do! The average is not 50%! Wow!). He was receptive to homework questions over email and I felt comfortable asking clarification questions during class. He followed the textbook which was pretty good for concepts so definitely don't get too behind on the readings (He likes True/False questions and the book is really helpful for those!). He is open to not including highly computational chapters on tests (like matrices or stuff that can't really be done outside R) but you have to push him a little to explicitly say something will not be covered or emphasized beyond basic concepts. R is an easy program to use, and homeworks are 100% doable on your own (also refreshing, as I felt like I couldn't get through 3105/3107 without looking most answers up on Chegg). Ronald goes through examples in class that help a lot with homework (again, what a luxury in the stats department...). Also, he had soft deadlines on ho…

Very reasonable. 7 assignments, all requiring R programming. Typically he would explain how to do any difficult questions the class before it was due. Midterms were multiple choice with some short answers and covered only material we learned. 10/10 would take again.

Ronald Neath is the best Statistics professor I have ever had at Columbia (unfortunately there isn't much competition). He came in excited and energetic everyday and was a clear and thorough lecturer. During class he would take notes on the board and later he would post handouts that would help us complete the homework assignments. Take him if you can!

7 applied HW assignments in R, two midterms - one final, everything doable.

This was a great class and Prof. Neath is a great instructor. Maybe not the best lecturer (IMHO Elbarmi is the best) but the best instructor overall considering lectures, assignments, availability, extra materials, exams and grading. If possible, I would take any class in the Statistics major with him. If you have the chance to fulfill a requirement taking one of his classes, DO IT.

All about linear regressions, from the basic model specifications to more complicated measures of outlierness like cook's distance. Overall a very comprehensive course about how and when to use linear models to fit to data.

I have learned plenty regarding applied LRM.

If you wanna learn some Regression and some R, this is the class for you. It gets a bit heavy when it comes to the Linear Algebra stuff, but otherwise, this course does it's job.

This course got me back on track with Stats! And I learned R! Despite the ever-present poor time slots for Stats department classes, I enjoyed this class dearly and was able to understand a lot of new concepts well.