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. Anthony Lee |
Open unit status | Not open |
Pre-requisites |
MATH10013 Probability and Statistics |
Co-requisites |
None |
School/department | School of Mathematics |
Faculty | Faculty of Science |
Lecturers: Anthony Lee and Skevi Michael
Unit Aims
To develop the theory and practice of basic statistical inference, and statistical calculation.
Unit Description
Statistics is about inference under uncertainty, ie in situations where deductive logic cannot give a clearcut answer. In these situations our decisions must be assessed in terms of their probabilities of being correct or incorrect. Such decisions include estimating the parameters of a statistical model, making predictions, and testing hypotheses. It is often possible to identify 'optimal' or at least good decisions, and Statistics is about these decisions, and knowing where they apply. A thorough grounding in Statistics, as provided by this course, is crucial not only for anyone contemplating a career in finance or industry, but also for scientists and policymakers, as we realise that some of the biggest issues, like climate change, natural hazards, or health, are also some of the most uncertain.
Relation to Other Units
This unit develops the Level 4 Probability and Statistics material, and is a prerequisite for some statistics units at Levels 6 and 7, namely Bayesian Modelling, Linear and Generalised Linear Models, and Theory of Inference.
Learning Objectives
By the end of the course the students should be able to:
Transferable Skills
A clearer understanding of the logical constraints on inference; facility with the R environment for statistical computing.
The unit will be taught through a combination of
80% Timed, open-book examination 20% Coursework
Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.
If you fail this unit and are required to resit, reassessment is by a written examination in the August/September Resit and Supplementary exam period.
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