Professor: Bienenstock Course format: Lecture w/section Number of respondents: 40 Total Enrollment: 102 Class Composition: Froshs: 0 Sophs: 24 Jrs: 46 Srs: 25 Concs: 9 Non-Concs: 26 Don't Know: 1

Instructor Average: 1.80 Course Average: 1.81

“Statistical Inference I” provides an introduction to mathematical statistics. The first half of the course covers probability and the last half covers statistics. The only prerequisite is Math 10, and students indicated that a general background in calculus was helpful in understanding the material.

Overall, reviewers were not impressed with Professor Bienenstock’s lectures. They commented that his lectures weren’t always clear and he often went too fast. The lectures were long and boring, and some felt that the professor did not speak clearly and that his handwriting was difficult to read. Students complained that he followed the book too closely and used the simple examples from the book, instead of presenting new, more challenging and applicable examples. Many also felt that he spent too much time on proofs and theorems without explaining them thoroughly or providing examples. However, class members felt that he was approachable and cared about the class, and was always receptive to questions. In general, students seemed to think that the lectures made material unnecessarily complicating and that it was more useful to just read the textbook.

The coursework consisted of two midterms, a final, and weekly homework assignments. Some students commented that the problem sets were tedious and took longer than expected, and a few thought that the first midterm was too easy, while the second one was too hard. Reviewers agreed that the textbook was very clear and helpful, and it was important to read the text as it clarified the lectures. A few noted that you could learn almost everything from the book instead of the lectures.

Students spent between three and six hours on this course, which seemed to match their expectations. If you have a strong math background and need to take statistics, this course might be for you, but if you are looking for something a little more applicable, you might want to try one of the statistics courses offered in a different department.

View AM/0165 in the Brown Online Course Announcement.