Professor: Bienenstock Course format: Lecture	Number of respondents: 48 Total Enrollment: 61
Class Composition: Froshs: 3 Sophs: 14 Jrs: 22 Srs: 14 Concs: 12 Non-Concs: 32 Don't Know: 0

Instructor Average: 1.81 Course Average: 1.79

"Statistical Inference I" is a course based around the study of probability and statistical methods. Topics include confidence intervals, hypothesis testing, and probability spaces. Many of the concepts are calculus-based, and so it is necessary to have some working knowledge of calculus before enrolling into this course. Survey respondents said one semester is sufficient, although more is always helpful.

Professor Bienenstock was generally regarded as a good teacher by the students in this course. Some felt that the pacing in his lectures was awkward, but the class itself was divided on wanting him to speed up or slow down. Despite the wide range of students, he made an effort to check with everyone on an individual level to make sure that they understood the material. Both sides said that his presentation of ideas was both organized and very clear. However, many felt that his lectures could be very boring at times.

The work for the course consists of weekly problem sets. Some found the problems slightly repetitive. There were two midterms and one final exam. Not everyone used the textbook much, but those who did felt that it was easy to understand and helpful as a reference.

Reviewers spent an average of five hours per week on the course, meeting expectations without exceeding them severely. Depending on the student, the actual time ranged anywhere from two to fourteen hours. This course is a good option for anyone interested in either Applied Math or a field that uses statistics heavily. People wrote that the work is sizable but not overbearing, and it gives a solid foundation for anyone pursuing more advanced statistics. If you have a desire to learn more about probability and statistics, give it a chance.

View AM/0165 in the Brown Online Course Announcement.