**Lectures:** Thursday, 4:30-7:10pm, Engineering Building, room 1108

Some of the lectures will be based on notes posted on this website. Some lectures will be accompanied only by notes written on the board.

If you send email to the instructor, please put "CSI 771" or "STAT 751" in the subject line.

The general description of the course is available at mason.gmu.edu/~jgentle/csi771/

**Prerequisites:
**

**Text:**
Computational Statistics
ISBN 978-0-387-98143-7.

We will cover most of Parts I, III, and IV.

**Software:**
The main computational software is R.

R is open source and is free. It is installed on some GMU computers, but there are various binary executables available at the main R website, and it is best to load it on your own computer.

A good way to learn R is just to use it for progressively more complicated problems. While there are many books on R, the various pdf manuals that come with the installation (use "Help" on the GUI) should be sufficient.

- a number of small assignments, problems, etc. (20)
- a
semester project to replicate and extend a published Monte
Carlo study (25)

Project will be graded on- design and conduct of the study
- written report
- presentation

- an in-class midterm (25)
- an in-class final exam (30)

The course requires each student to complete a project that involves a Monte Carlo study of a statistical method.

Each student enrolled in this course must assume the responsibilities of an active participant in GMU's scholarly community in which everyone's academic work and behavior are held to the highest standards of honesty. The GMU policy on academic conduct will be followed in this course.

Group work and discussion outside of class is encouraged, but of course explicit copying of homework solutions should not be done.

For in-class exams, one sheet of notes will be allowed. The preparation of that sheet is one of the most important learning activities.

General introduction; Appendix A; R

Brief introduction to R.

R functions.

Random number generation in R.

**Assignments:** Read Appendix A (page 643); work problem 1.18 (page 77) to
turn in (in hardcopy on September 10).

Chapter 1

Statistical inference.

The role of optimization in statistical estimation:
minimization of residuals;
maximization of likelihood; etc.

The functional approach to statistical estimation.

**Assignments:** Read Chapter 1; work problems 1.15, 1.16, and 1.21 to
turn in (in hardcopy on September 17).

Chapter 9; review Section 1.2; parts of Chapter 5

Linear transformations.

Measures of similarity.

**Assignments:** Read Chapter 9; work problems 1.5, 5.1, 9.1, 9.2, and 9.13 to
turn in (in hardcopy on September 24).

Chapter 10; parts of Chapter 4

**Assignments:** Read Chapter 10; work problems 10.1, 10.3, and 10.4 to
turn in (in hardcopy on October 1).

Begin Chapter 11; review Appendix A

Sample from a previous year.

Chapter 11; Chapter 12

Discuss semester project (Exercises A.2 and A.3)

Monte Carlo methods of inference

**Assignment:** Exercise A.2, with just 2 articles, and can be
some other statistical journal.

Chapter 7, Chapter 12

Methods of transforming uniform random variables to random variables from other distributions.

Data partitioning; jackknife methods.

**Assignment:** Work problems 7.2, 11.3, 11.7, 12.1, and 12.6 to
turn in (in hardcopy on October 29).

Chapter 13

Additional reference: Maria L. Rizzo (2007) Statistical Computing with R

Also see R programs at author's website.

**Assignment:** Work problems 13.1, 13.2, and 13.8 to
turn in (in hardcopy on November 5).

Chapter 14; Cahpter 15

**Assignment:** Work problems 14.1, 14.2, and 15.1 to
turn in (in hardcopy on November 12).

Chapter 15, Chapter 16

Statistical learning.

**Assignment:** Work problems 15.2 a) and b), 15.11, 15.13, and 16.1 to
turn in (in hardcopy on November 19).

Solutions; comments.

Chapter 16

Statistical learning: ordering multivariate data; principal components; projection pursuit. We did not have time to discuss projection pursuit, so it will not be considered to be part of the course.

**Assignment:** Work problems 16.5 and 16.7 a) to
turn in (in hardcopy on December 3) and work problem 16.8 not to turn in.

Solutions; comments.

**Assignment:** Work problem 16.6 (not to turn in).

Chapter 17

Closed book and closed notes except for one sheet of prewritten notes.