Module Descriptor School of Computer Science and Statistics
|Module Name||Base Module (Post Graduate Certificate in Statistics)|
|Module Short Title||N/a|
|Contact Hours||Lecture hours:44|
|Module Personnel||Lecturing staff:: Gerard Keogh|
On successful completion of the Base Module students should be able to:
They will have a sound basis on which to develop further their statistical skills.
The base module is introductory and will lay down the foundations on which other modules will build. The fundamental statistical inferential ideas of significance tests and confidence intervals are the central topics. The various inferential methods will be unified through the concept of a statistical model, which is an abstract representation of the quantity we wish to describe. For example, we may choose to represent the weights of filled containers by a Normal distribution with a particular centre (mean) and measure of spread (standard deviation). This would allow us to introduce formal tests to determine when the process average weight changes.
Specific topics addressed in this module include:
|Recommended Reading List|
The course notes are extensive and are the primary source material needed for the course. The following book is a suitable general reference for the base module.
My own book was written for analytical chemists, but it would be suitable reading for most natural scientists and engineers. Moore and McCabe would be more suitable for social scientists.
Those with medical interests will find the following a useful reference book:
% Exam: 100%
|Academic Year of Data||N/a|