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
- Interpolating, smoothing, and numerically
- Random number generation and Monte Carlo
- 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.
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.
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.