|Module Title||QUANTITATIVE BIOLOGY AND INFORMATION TECHNOLOGY|
|Co-ordinator||Dr Iolo Ap Gwynn|
|Semester||Semester 2 (Taught over 2 semesters)|
|Other staff||Dr John Gee, Mr Alvin Jones, Dr Paul Kenton, Dr Michael Winson, Dr Robert Wootton|
|Pre-Requisite||BS12410 Information Technology & Quantitative Biology|
|Course delivery||Lecture||29 Hours|
|Practical||22 Hours 11 x two hours (6 IT & 5 QB)|
|Assessment||Exam||3 Hours One 3-hour theory paper||50%|
|Practical exercise||Continuous assessment of practical work||50%|
|Resit assessment||3 Hours One 3-hour theory paper (plus resubmission of failed coursework or an alternative)|
Aims and objectives
This module builds on Module BS12410 - Information Technology and Quantitative Biology and brings the student to the level of mathematical competence and acquaintance with information technology to be expected of a modern biologist. As such it will provide a package of skills that are potentially transferable to a wide range of employment situations.
Quantitative Biology (general): Calculus; the gradient of a curve; asymptotes; differentiation of polynomial and exponential functions; maxima and minima; a brief introduction to integration - the indefinite and definite integral. An introduction to mathematical modelling - based on population growth and/or a physiological process
Quantitative Biology (statistics): Sampling distribution of the mean: the standard error of the mean.
Hypothesis testing, type 1 and type 2 errors in significance tests, one-sample and two-sample t-tests of means, confidence intervals. Concept of replication; avoidance of pseudoreplication. Bivariate samples and populations; the correlation coefficient, test of significance. Non-parametric methods, emphasising analysis of contingency tables. ANOVA, taken as far as two factor designs and the concept of an interaction, and explaining partitioning of the sums of squares and the relationship with the t-test. Linear regression and its relationship with ANOVA (including fitting the line, testing significance, standard errors of parameters, confidence bands, comparing regression slopes, direct test of linearity). The emphasis will be on interpretation of results and will include examination of residuals.
Information Technology: Spreadsheet software (introduced in BS12410) will be used and Minitab will be introduced within the quantitative biology elements. Word processing skills (introduced in BS12410) will be extended during the IT sessions by application to other topics.
A variety of software will be introduced in the context of applied biological uses. The following aspects will be covered:
Database creation, searching and management, including the use of Internet databases.
Complex vector graphics, leading to the preparation of biological drawings.
Bitmap graphics, and their uses - including image processing and analysis.
Presentation software (PowerPoint) for the preparation of slides and live presentations- includes design principles and the use of animations.
Preparation of Web pages - essentials of HTML and file management.
(Students will be expected to process data for and present their third year projects, utilising the skills that will be taught in this module, including slide preparation using PowerPoint or equivalent).
On completion of the module, students should be able to
** Reference Text
Zar, J.H.. Biostatistical analysis. Prentice Hall.
** Should Be Purchased
Dyntham, C.. (1999) Choosing and using statistics: a biologists guide. Blackwell Science.
O'Leary, T.J. & O'Leary, L.I.. (1999) Microsoft Office 2000 Professional. Irwin McGrawhill.
Causton, D.R.. (1983) A biologists basic mathematics. Arnold.