course
Statistical Inference

One of the best professors ever had! He made those hard concepts easier to understand. He does have some accent but I got used to it in a week. The solutions to homework are clear, but the TA doesn't tell you what's wrong. The midterm was really easy and very similar to the practice midterm. He really cares about students, and always makes sure we understand the concepts, and he's always willing to rephrase it if we seem confused.

This course is a must for anyone who wishes to do anything related to statistics, so I have no regrets about taking it. Prof. Hueter is not exceptional or insightful but overall her teaching is solid. She also seems like a very nice and kind person, though not very approachable. Her teaching is sort of mediocre, but I enjoyed that she went through the material slowly and gave lots of examples in class (she increased the speed significantly towards the end of the course though as we were running behind the syllabus schedule). I had absolutely terrible background in probability theory (thanks stats department!) but I managed to understand the course material and even learn the probability material during this course. I wish that she put more effort into designing homeworks as they were simply problems from DeGroot and were sometimes not very related to the class material.

Hueter is one of the worst professors I've had at Columbia. Her apathy toward her students was palpable from day one. "Don't expect even a response from me via email", she announced the first day of class, asserting that her commitments to statistical consulting left her far too drained to deal with questions from her students. Why is she bothering to teach if she already has a full-time job? It is important to give her some slack as English is likely not her first language, but some of the her words come across as downright hostile. On top of this, she is incredibly lazy in presenting the material. She reads straight from the PDF notes used by ever other inference professor for the last few semesters in the most monotone way possible. She is not a glaring anomaly in the hotbed of incompetence that is the statistics department, but she certainly shouldn't be teaching what is the most important statistics course for undergraduate majors. She shouldn't be teaching at all, frankly.

Prof. Neath is just overall a bad explainer of things. During the first few classes I went and tried to concentrate and follow through. I couldn't. He rushed through everything as if his life depends on writing down those arcane formulas and 4-board-long proofs on the boards and nothing else - because that's exactly what the does every class. To do him justice he does try to explain what he writes, but far from successfully, as I always find the book easier to follow than his lecture. He does not try to break down difficult concepts with easy-to-understand examples, but instead, he expects you to have an intuitive sense of what's going on right off the bat/from reading the formula itself. So after presenting the formula without any effective explaining, he goes straight to the hardest, most advanced applicable example of this formula and boom every single one is confused, even those who were starting to gain a vague idea of this concept. Now I haven't finished the course yet, but I got a solid A and 95+ on the final (class avg 60-70) for the prereq of this class (4203/5203 Probability Theory) and had a data-intensive internship the summer prior to taking this class, so if I couldn't follow through or understand ANYthing on his lecture but only managed to understand everything through the book, there MUST be something wrong on Prof. Neath's side. If he'd be reading this, I just have one suggestion: please understand that your students don't have the decades of familiarity with all these formulas which do not come naturally at all. Treat them with some sympathy, slow down and supply some intuitive examples. I.e., actually give some crap about the students.

tldr: Great Professor. Nothing much more to say. Dr.Young is an extremely solid professor. He is able to communicate complicated statistical concepts and dry mathematical derivations in a concise and dare I say interesting manner. He has mastered the ability to quickly explain the small math tricks he uses without getting completely bogged down. Unfortunately, a lot of the material is inherently boring, so this class won't change your life or major, but it gives you a solid understanding of statistics and thinking problematically. Honestly, I learned more about probability theory in this class then I did in probability theory. The best thing about Dr. Young's class is the textbook. Casella and Berger are extremely clear and rigorous. Their examples are fully worked and challenging enough such that understanding all the examples guarantee that you'll do well on the homework and exams. Also the textbook is used in PhD level courses so you can be a little confident in the rigor. Finally, don't worry about him scaring you that he doesn't curve the test scores. HE MOST DEFINITELY DOES. Also if you're someone who struggles with math, you might want to take Calc IV before this course.

Mazumder is a new professor, Fall 2013 was his first semester at Columbia and it showed. In a number of ways it felt like he was trying to figure out how Columbia worked, and how he wanted to structure the class, as we went along. The good news is that it was generally improving, the bad news is that it started pretty poorly. He used Casella and Berger, a great and very standard book. I think it's slightly more advanced than many 4107 classes, but it's really the book they all should be using. The descriptions can be terse, and it lacks examples at times, but it's generally well written and rigorous. Lectures were largely LaTeX slides based on the Casella and Berger examples, and posted online (usually after class). He used the blackboard frequently, and I generally found that more useful than the slides. I found the lectures mixed in terms of learning. Sometimes they were really helpful, often I felt like I didn't understand the point. Frequently his examples would be all very similar, and I wouldn't understand the limits of a theorem. He would often use very similar examples (ie only use the normal for a certain theorem), and it wasn't clear what was specific to the normal, and what wasn't. The January 15 review describes the midterms reasonably well. The first one was punishingly difficult and graded leniently. The second was much easier, it felt like it was from an entirely different section, but graded much more strictly. The final was in between, and didn't focus on the stuff I expected (e.g., no regression). I found the homeworks hard, very time consuming, and felt unprepared for them. Office hours, when I could make them, were generally too crowded for me to get meaningful help. I ended up using the Casella and Berger solutions for hints when I got stuck frequently. Toward the second half of the class he started writing his own questions, which were similar to the C&B questions, maybe a touch easier. In general he seemed fairly motivated to teach, and I think he improved during the semester. I would guess in another few semester he would be perfectly fine, at least compared to other stats professors here.

He teaches this class at a pretty theoretical level. I'm not sure how to feel about that... In any case, his lecture notes come from the textbook for the most part--he posts his powerpoints online. HW comes right out of the textbook and was graded pretty leniently. His first midterm was pretty brutal. Average was like a 30%. It had a lot of tricks and stuff that was not explicitly taught in class--you moreso had to apply the basic concepts in class in a way that you might not have expected. Second midterm was a lot easier--questions were pretty similar to examples done in class/basic concepts. Overall, second midterm was more straightforward--average was around a 50, I think. Final was also pretty straightforward, I thought. It had a few parts of questions similar to midterm 1, but for the most part I felt like it was similar to midterm 2.

He's a nice guy and tries to make sure everyone understands. Unfortunately for my class, this meant that we spent most of the time doing probability (4105 stuff) and didn't cover half of the material for statistical inference. He tried to hurry his pace and started using to present slides to save time from writing on the board. At some points, he showed pages from the book as well. Any material we didn't cover was assigned as a project or self study with homework. Also, there would be questions asked during class that he wouldn't be able to answer, more than any other class I've taken. The material is not any harder than 4105. The book by hogg and craig is fine. It's harder than Degroot & Schervish [4109] but easier than Casella & Berger [PhD book]

I had this professor for 4107 Fall 09. It was a total waste of time. It's probably a good brush up course if you already know the material. But if you want to learn something, you are out of luck. I truly wonder how many people actually understood what he was attempting to communicate in class. The failure comes mostly from his nonchalant attitude to the teaching responsibilities. I don't think he put in much time preparing for the class, even after almost everyone flunked the midterm. The students are left in chaos as the class material, homework and exam only remotely correspond. I don't mind tricky questions, but they only make sense when the basic concepts have been grasped. The truth is with this class, you struggle after class and spent much time on your own just to get the basic concepts. The Prof's teaching is not contributing anything in that regard.

I totally agree with the review about him. I was in his fall 2009 Stats Inference class, and it was a totally painful expireance. Schnaidman works in industry, and it was clear that he ran the class as an after thought. He used another professor's notes and read straight from them. He would literally list off theorems. After a while, most people stopped going to class, or showed up periodically for the announcements. The notes didn't really match the content of the class, and were pretty theoretical. Everyone was stumped by the midterm (he doesn't teach us anything, and throws tons of curveballs on tests). The class was completely disorganized, with most people feeling like they were failing. I think he's probably going to have to curve a lot in the end, but it still won't be worth the miserable experience.

I had this guy for W4107-Statistics in the Fall 2009 semester. He was a horrible professor, spending all of the lecture time reading word-for-word off of a PDF document that listed key definitions and theorems from our textbook. He clearly did not put much effort in the class at all, and did not believe he should be putting any effort into lecturing because he thought it was the students' responsibility to ask questions if things were not clear. The best part of the class was that we used Casella and Berger's Statistical Inference textbook, which has a handy solutions manual for the majority of the problems. The worst part of it is that we essentially did one chapter a week, covering chapters 1-9 over the course of the semester. The mid-term covered Chapters 1-4, and the final exam was cumulative, with focus on Chapters 5-9.

Professor Hernandez is a really nice professor. He truly cares whether you understand the material or not. He tries to make the classes interactive. If you tell him that he's going too fast, he will slow down. He listens to his students' needs. Yes, he is a little disorganized sometimes but that doesn't affect his teaching ability. If you don't understand something, he'll try his best to help you understand. What is said about his accent is ridiculous. While he has an accent, he's fluent and his accent is mild. I would highly recommend that anyone take this class with him. I'm taking another class with him next semester.

Kamiar is NOT a professor. He's a grad student. He has a heavy accent, is completely lifeless and dull. He was our TA for W4107 (Statistical Inference). He intentionally kept unreasonable office hours, even though all of us asked for a different time. He said he would be available by appointment but that didn't work either. One time he tried explaining something but didn't make any sense.

Terrible Professor. Didn't teach the material at all, and instead assumed that the students would learn all of the information through the textbook which was way above our level. Weekly homework's which were tough, but some of the solutions were in the solution manual (Buy this!). Midterm was taken straight from the homework, literally the same problems. No Final exam, instead an easy final project.

There is a reason that Prof. Dan Rabinowitz is the chair of the Stats department. He is amazing! He's great at explaining complex theories, using everyday common analogies to convey his points. However, the material is hard! He assigns homework to help you with the theories, but the great thing is that poor homework (or no homework at all) does not affect your grade. BUT I URGE YOU TO DO THE HOMEWORK OR YOU WILL BE LOST!

Flippin hard material! Before you read this, be aware that I am an undergrad who was forced to take this class because i couldnt fit anything else in my schedule. Most people in this class were bschool and stats masters, so I am speaking from an undergrad perspective (therefore others may have found the course easier than I did). Professor Paninski is a cool guy, very laid back and friendly. I think this was his first time teaching as well. The course material was quite difficult and I had a hard time following him. The theme of the class was "oh, well if you see my mistake, let me know" or "ya, well it looks something like that." Anyone who takes math classes knows these statements tend to pop up. I felt they popped up a little to often in this class, usually to the point that it was hard for me to grasp what was right and what was wrong. The real problem with his teaching style is something alot of teachers have, he sets the bar way too high. He doesn't do any examples of the theories taught in class, leaving students to fend for themselves. The homework problems were explained by teh TA, and if you miss recitation you will be clueless (as i was) on all of them.