Course Information

Learning Goals

The primary objective of this course is to provide a strong foundation into fundamental statistical concepts, particularly as they relate to genomics, and thus better prepare you for a successful scientific career.

Required Texts and Online Resources

There is no required textbook for this course. Each lecture will be accompanied by a handout that covers all of the in class material. There are also several excellent introductory statistics resources available on-line. The following websites contain on-line textbooks that cover all of the material presented in this class.

For students who would like to have general reference book, I recommend:

Probability and Statistics for Engineering and the Scientists 6th Ed. Jay L. Devore (2004). Duxbury press, Thompson-Brooks/Cole.
Statistical Inference. Casella, G. and Berger, R. L. (1990). Wadsworth, Belmont, CA.
Probabilistic Graphical Models: Principles and Techniques. Koller, D. and Friedman, N. (2009). MIT Press.

Grading

Grades will be based on five problem sets that will each comprise 20% of your total grade. Problem sets will be distributed on Thursday and due the following Thursday at the start of class. Late assignments will not be accepted in general. It will be only accepted in exceptional circumstances or if prior arrangements have been made with the instructor.

Class Meetings

Class meets twice a week – Tue/Thu 9:00-10:20am in Foege S110.

Each class will last for 80 minutes and be primarily lecture based, but will include other forms of learning and interactions. In particular, we will often interrupt lectures to work on problems in small groups as well as work through statistical analyses using the freely available software R.

Instructor