## Statistics 604: Introduction to Computational Statistics

### Content of the Course

- Essential algorithms used in
carrying out statistical methods, including:
- Evaluating pdf, cdf, and quantile functions
of distributions.
- Interpolating, smoothing, and numerically
integrating functions.
- Random number generation and Monte Carlo
simulation.
- Sorting, searching, and data base manipulations.
- Matrix algebra and its application
to regression and analysis of variance.
- Nonlinear optimization.
- Algorithms in mutivariate analysis.
- Algorithms in time series analysis.
- Computer graphics.

- Creating statistical software on graphics workstations
(PC's and SUN's), including:
- Introduction to Fortran (and maybe C).
- Writing simple interactive graphics programs.

- Using "matrix oriented" software, including Splus.
- Using the TeX text formatting and typesetting program.
- Becoming familiar with our Unix workstation network
including e-mail, ftp, statlib, etc.

### Course Materials

I have prepared a set of notes to be used in the course. They are on the
STAT 604 web page and can be printed, either by chapter or all together.
### Prerequisites

Knowledge of distribution theory and regression analysis (using
matrices) such as covered in STAT 601 is assumed. Previous
exposure to a high level programming language such as C, Pascal,
or Fortran is helpful but not required. No previous exposure to
matrix oriented languages is assumed.
### Determining the Course Grade

There will be two in-class, closed-book exams and a final. Each
of these three exams will be worth 20% of the grade and will
cover algorithms primarily. There will also be a series of
programming projects, worth a total of 40% of the grade.