Statistics
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Department of Mathematics & Statistics

## STAT380 Statistical Computing

 First Semester
18 points
Not available after 2018

This course develops a working knowledge of several topics in modern statistical computing. We focus on a practical understanding of how and why such methods work rather than their analytic bases. A second aim is to learn a suitable language that allows computer implementation of the statistical ideas covered.

### Potential students

This paper is intended for students with some exposure to statistical techniques.

### Prerequisites

STAT 241 + 18 additional points of 200-level statistics

### Main topics

• Introduction to R
• Bootstrap and randomization procedures
• Optimization, numerical integration and maximum likelihood estimation
• Simulation and MCMC methods

### Required text

There is no prescribed textbook, but some texts that may be useful include:

• Peter Dalgaard, Introductory Statistics with R, Springer, 2002. ISBN 0-387-95475-9.
• Anthony Davison and D.V. Hinkley, Bootstrap Methods and their Application, Cambridge University Press, 1997.
• Geof H. Givens and Jennifer A. Hoeting, Computational Statistics, Wiley, 2005. ISBN 0-471-46124-5.
• William N. Venables and Brian D. Ripley, Modern Applied Statistics with S, Fourth Edition, Springer, New York, 2002. ISBN 0-387-95457-0.

### Lectures

Monday and Wednesday at 9:00 - 9:50 AM; room B21. These are compulsory.

### Tutorial/Practical

Tuesday at 9:00 - 9:50 AM; room B21. This is compulsory.

### Internal Assessment

The internal assessment will make up 40% of the final mark. Six assignments will make up a total of 25% of the final mark. A mid-term test will make up 15% of the final mark.

### Exam format

The final exam will be worth 60% of the final mark. A minimum score of 40% is required on the exam in order to pass the paper.

### Final mark

While we strive to keep details as accurate and up-to-date as possible, information given here should be regarded as provisional. Individual lecturers will confirm teaching and assessment methods.