Math 1620: Mathematical Statistics


"There are no data that cannot be plotted on a straight line if the axes are chosen correctly. "

Professor Richard Kenyon
Tel. 863-6406
rkenyon -at- math.brown.edu
office: Kassar 304
Office hours: Mondays 11:30-12:30 (Monday 2/11: 11:30-12:00)

Isaac Solomon
Tel. 863-3560
yitzchak_solomon -at- brown.edu
office: Kassar 018
Office hours: TBA

Texts: Larsen and Marx, An Introduction to Mathematical Statistics and its Applications, 5th ed.
Pattern Recognition and Machine Learning, C. Bishop

Course outline: The first part of the course will cover Estimation, Hypothesis Testing and Regression from a rigorous point of view. The second will focus on data analysis, pattern recognition, classification, discriminant analysis and other topics as time permits. The course will be taught by Richard Kenyon and Isaac Solomon.

There will be homeworks collected weekly and one midterm. There will be (depending on class size) a written final project. The final grade will be weighted as follows: Homework 35%, midterm 30%, final project 35%.

Midterm:

March 12 in class.

Homework:

Late homework will not be accepted. The lowest homework grade will be dropped.
It is expected that your homework should involve up to 10 hours of work per week.

Homework 1: due Tuesday Feb 5 in class
4.2.26, 4.3.2, 4.3.4, 4.3.9, 4.4.2
5.2.2, 5.2.3, 5.2.8

Homework 2: due Tuesday Feb 11 in class
5.2.12, 5.2.16, 5.2.18,
5.3.4, 5.3.5, 5.3.11, 5.3.19, 5.3.24, 5.3.26

Homework 3: due Thursday Feb 20 in class
5.4.2, 5.4.3, 5.4.14, 5.4.19, 5.5.2, 5.6.4, 5.7.2

Homework 4: due Tuesday Feb 25 in class (make sure you are using 5th edition!)
5.8.1, 5.8.3, 6.2.2, 6.2.4, 6.2.6, 6.2.9

Homework 5: due Tuesday Mar 5 in class (make sure you are using 5th edition!)
6.4.5, 6.4.8, 6.4.13, 6.4.18, 6.5.1