|| BS22720 |
|| QUANTITATIVE BIOLOGY AND INFORMATION TECHNOLOGY |
|| 2003/2004 |
|| Dr Iolo Ap Gwynn |
|| Semester 2 (Taught over 2 semesters) |
|| Dr John H R Gee, Dr Michael K Winson, Dr Paul Kenton, Dr Robert J Wootton |
|| BS12410 Information Technology & Quantitative Biology |
| Course delivery
|| Lecture || 39 Hours |
|| Practical || 10 Hours (5 x 2 hours) plus optional 12 hours workshops (6 x 2 hours) |
|Assessment Type||Assessment Length/Details||Proportion|
|Semester Exam||3 Hours One 3-hour theory paper ||50%|
|Semester Assessment|| Practical Exercise: Continuous assessment of practical work ||50%|
|Supplementary Assessment||3 Hours One 3-hour theory paper (plus resubmission of failed coursework or an alternative) || |
On completion of the module, students should be able to
apply the wide range of mathematical and statistical skills, not only required of a modern biologist but also required in a wide range of fields
use a personal computer for database management, processing and analysis of images and to create vector drawings
use the Internet for data searching
prepare and deliver presentations using advanced IT skills
prepare HTML files, with associated graphics, for preparation of Web pages.
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 )
ATTENDANCE AT LECTURES & PRACTICALS
Attendance at lectures will be checked.
Absence from practicals, without good reason, will result in work from that practical not being assessed. Exceptions will ONLY be made where there are extenuating circumstances approved by the Director.
** Reference Text
Zar, J.H. Biostatistical analysis
** Should Be Purchased
Dyntham, C. (1999) Choosing and using statistics: a biologists guide
O'Leary, T.J. & O'Leary, L.I. (1999) Microsoft Office 2000 Professional
Causton, D.R. (1983) A biologists basic mathematics
This module is at CQFW Level 5