MAS8401 : Numeric Skills (Statistics and Mathematics)
- Offered for Year: 2019/20
- Module Leader(s): Mr Aamir Khan
- Lecturer: Dr James Waldron
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
|Semester 1 Credit Value:||10|
|Semester 2 Credit Value:||5|
To introduce fundamental statistical and mathematical concepts and techniques of importance in Bioinformatics.
This module provides an introduction to the basic statistics and mathematics skills that you need for bioinformatics and computing. The module runs over the whole year, covering statistics first and then leading into aspects of discrete mathematics.
Outline Of Syllabus
Introduction to data analysis; probability axioms; combinatorics; conditional probability; discrete probability models; continuous probability models; properties of estimators; unbiased estimators; sampling distributions; central limit theorem; maximum likelihood estimation.
Set theory (basic sets; functions; relations);
Automata (finite state machines; languages and grammars);
|Scheduled Learning And Teaching Activities||Lecture||36||1:00||36:00||Formal lectures|
|Scheduled Learning And Teaching Activities||Practical||6||1:00||6:00||Computer practicals|
|Scheduled Learning And Teaching Activities||Small group teaching||18||1:00||18:00||Seminars|
|Guided Independent Study||Independent study||1||45:00||45:00||Written assignments and CBAs|
|Guided Independent Study||Independent study||1||45:00||45:00||Studying, practising and gaining understanding of course material|
Teaching Rationale And Relationship
The statistics element will be taught mainly via lectures with additional seminar discussions and computer practicals to reinforce both technical and practical aspects. The mathematical element requires more formal teaching through lectures and also discussion in seminars.
The format of resits will be determined by the Board of Examiners
|Prob solv exercises||1||M||66||N/A|
|Prob solv exercises||2||M||34||N/A|
Assessment Rationale And Relationship
This module is entirely assessed by coursework. In Semester 1 there are approximately 6 written assignments of approximately equal weight. In Semester 2, the nature of the material changes and the coursework changes to reflect this, with two written assignments of approximately equal weight.