| Unit name | Statistics 2 |
|---|---|
| Unit code | MATH20800 |
| Credit points | 20 |
| Level of study | I/5 |
| Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
| Unit director | Professor. Andrieu |
| Open unit status | Not open |
| Pre-requisites |
MATH 11340, MATH11002 and MATH11003 |
| Co-requisites |
None |
| School/department | School of Mathematics |
| Faculty | Faculty of Science |
Statistical inference deals with the interpretation of sets of data that contain some random variation. It is an essential tool for anyone contemplating a career in finance, commerce or industry. However, there are often no clear-cut answers to the natural questions of interest, and two contrasting approaches have been developed - the frequentist and the Bayesian. It is important to understand what questions can be answered by each method and how the methods differ. This unit will develop the ideas introduced in the latter part of the first year unit, using practical examples to clarify the underlying theoretical results, and will provide a foundation for students taking later applied statistics units. It will cover the principles, the techniques and the optimality properties of the two approaches to Estimation, Hypothesis Testing and Confidence Intervals. The only essential prerequisite is the first year unit in Probability and Statistics.
