January 01, 2006

Kou, Steven
Stochastic Modeling

Please keep in mind that this review is more than 5 years old.

Not a very good instructor, but the advantage is that you don't have to pay any attention in class and its the same as if you sit in the front row center. You have to go to class though because there are about 10 pop quizzes over the course of the semester. Kou is a very nice guy, but he moves quickly and doesn't really relate the material well. The Stochastic Models topic itself is very difficult and not very interesting. The way Kou conducts the class though makes it much easier than it could be.

Workload:

10-11 Quizzes. 1 Midterm. 1 Final. HW about every week. Curves to a B+.

December 24, 2005

Kou, Steven
Stochastic Modeling

Please keep in mind that this review is more than 5 years old.

Good guy, but can be hard to understand. He's young, eager, and can be strict. The class sucks and Kou doesn't make it any easier to understand. Of course, the book is even worse. But if you get the material, or get half of it, everything will be fine. Go to class, study the homeworks & practice test, and don't worry if you get a 40% on a test because it's probably still an A.

Workload:

Pop quizzes almost every class, impossible problem sets that he gives answers in class too, and a hard but generously curved midterm & final.

June 27, 2004

Sigman, Karl Silver_nugget
Stochastic Modeling

Please keep in mind that this review is more than 5 years old.

Sigman's lectures were very good becuase he went through each stochastic topic very slowly and made sure everyone understood it. His lectures are truly amazing and very easy to follow. Make sure you go to all of the classes and you shouldn't have a problem geting a B or higher in the class. He wants you to do well. The class was a 2 and a half hour one day a week type deal but he would come 15 minutes late and end the class 40 minutes early so it was awesome.

Workload:

Most of the homeworks were pretty easy, towards the end it gets a little harder but manageable. 2 midterms that were easy and a hard final. The first midterm was very simple and the second one and the final was harder because the mean was too high on the first

May 14, 2004

Whitt, Ward
Stochastic Modeling

Please keep in mind that this review is more than 5 years old.

Good Professor / stand-up comedian. He really likes to bring his sense of humor into the classroom, which is a good thing. Class is very straightforward. Each class you do about one example from the book in full detail. Course is pretty easy, but you will learn all about stochastic models, which is a very useful skill.

Workload:

Optional (total hookup) homework sets. Since the solutions are posted, you can not do them and them learn how to do the problems before the tests. Tests are pretty easy. Overall, the class is pretty easy, the professor is a great and really funny guy, and the subject matter is (renewal)rewarding.

May 10, 2004

Sigman, Karl Silver_nugget
Stochastic Modeling

Please keep in mind that this review is more than 5 years old.

Probably the most interesting class I've taken at Columbia. Sigman is a very good lecturer and tries to make the class interesting, even though the material isn't that exciting. Take any class you can with him!

Workload:

not too bad, hw every week or so, 2 midterms, final

June 01, 2003

Whitt, Ward
Stochastic Modeling

Please keep in mind that this review is more than 5 years old.

Like most engineering classes, attendance is an exercise in futility. Ward WhittÂ’s class is no exception. However, unlike most engineering classes, one comes out with a perception that one has certainly picked up a couple things along the way, as opposed to a false sense of gratification from passing the midterm and final as a result of being pulled up by the generous curve that evolves from SEAS studentsÂ’ indifference toward coursework and anything else academic.

The lectures are invariably incomprehensible, and the text – Sheldon’s Ross’ Introduction to Probability Models – is inevitably indecipherable. The problem sets, however, provide most of the instruction. Some of the problems are just too much to ask for from even grad students; others clearly impart a process and knowledge about whatever is supposed to be going on in the class.

A warning however: in order to save yourself some time (and a lot of anguish) – do well on the midterm. For those who had decided to slacked off, the rest of the post-midterm course becomes a sort of remedial program for those not quite up to snuff in their stochastic modeling “skillz” – surprise quizzes, supplementary problem sets, in addition to the regular assigned problem sets.

Workload:

The workload is fair and challenging: weekly problem sets (25%), a midterm (35%), and a final (40%).

Directory Data

Dept/Subj Directory Course Professor Year Semester Time Section