The best aspects of this course included the interesting material, available extra credit, and exercises that helped students conceptualize the subject matter. Some students felt the lecture slides were too often inaccurate, and the example derivations were exceptionally difficult to follow. Some students also felt the lectures were too theoretical. Suggestions included utilizing Blackboard and incorporating more application processes into each class. Prospective students should know this course is reading-intensive.

The highlights of this course were the overview to stochastic processes, the wide applicability of the topic, and the tools for success provided by the instructor. Lecture notes are provided prior to class and the lowest exam score is dropped. The worst aspects of the course were the lengthy homework, the lack of solutions or feedback on practice problems, and the teaching methods of the instructor. Some suggestions for improving the course include working through problems on the board, providing solutions to the practice problems, and focusing on more practical rather than theoretical problems. Prospective students should know this is a challenging course which will require a good deal of work outside of class between homework and studying.

The best aspects of the course were the availability of lecture notes before class and the interesting and relevant course material. Students found lectures to be hard to follow and boring at times. Grading by the TAs was harsh and inconsistent. Suggestions for improvement included having clearly outlined expectations of important information to know and a common, clear grading scale across all sections. Students also suggested working out more problems on the chalk board in lecture and providing solutions to practice problems. Prospective students should be comfortable with introductory