### 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 30%.

## 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