The fifth part of the course is concerned with statistical methods for inducing causal models of how our systems work. The course is meant to be practical. It emphasizes techniques, tactics and case studies. Some of the examples in my lectures are from Artificial Intelligence, but the course is more general in its scope, and I encourage students from other areas of computer science to take it. The text is my own.
Course requirements Three homeworks, one midterm exam, one final exam.
Your score on an optional term project can substitute for your score on either exam, or can count as extra credit. The project should involve a thorough empirical study, or development or review of empirical methods. Because in the past students have started the projects late and requested Incomplete grades, none will be accepted unless a one-page project proposal is turned in before the midterm exam. The exams will cover the assigned readings and lectures, with emphasis on the readings. The exams will also cover the appendices to chapters 6,7, and 8.