|| BSM2710 |
|| DATA MANAGEMENT AND HANDLING |
|| 2007/2008 |
|| Dr Michael K Winson |
|| Semester 1 |
|| Dr David R C Causton |
| Course delivery
|| Lecture || 15 Hours. lectures |
|| Other || 8 Hours. (4 x 2 hours workshops) |
|Assessment Type||Assessment Length/Details||Proportion|
|Semester Assessment|| Open book assessment ||70%|
|Semester Assessment|| Data analysis exercise ||30%|
|Supplementary Assessment|| Open book assessment ||100%|
Learning outcomesOn successful completion of this module students should be able to:
Demonstrate an understanding of the logic behind the selection of analysis methods for data sets.
Assimilate and evaluate data for subsequent interpretation and analysis.
Devise testable hypotheses, define focused aims and objectives.
Demonstrate proficiency in applying statistical and research methodologies.
Conduct research searches using library, Information Technology and database sources.
Collect, store, analyse and interpret data.
Utilise appropriate bioinformatics resources for gathering and analysing information.
This module addresses the important issue of dealing with scientific information in the form of data. It aims to introduce biologists to the concepts and terminology of statistical science which will enable students to have meaningful dialogue with professional statisticians in considering experimental design and data analysis. Introductions to data management, bioinformatics and Intellectural Property (IP) issues will be provided in the form of workshops. Students will be provided with an overview of good practices, limitations of data and use of appropriate statistical analysis to gain information from data which allows hypothesis testing and valid conclusions to be drawn. The module covers different types of data and standard, mainly parametric, statistical approaches. The teaching of this section of the module is based firmly around appropriate worked examples. The aim of the workshops is to provide practical experience in the use of bioinformatics, data archiving and multivariate data analysis, including use of computer software packages, and to focus on IP issues in data acquisition and management.
The lectures cover the following topics:
Descriptive Statistics - Samples & Populations
Inferential Statistics - Hypothesis Testing & the setting of Confidence Intervals
General principles of the design of experiments and surveys
The analysis of variance: one-way, two-way and two factor
Regression, including multiple regression
An introduction to Multivariate Methods
Analysis of variance and regression will be instructed via Excel.
Workshops cover the following topics:
Information access and bioinformatics
Intellectual Property and licensing issues
Data acquisition and archiving
Use of PCA/DFA/PLS analysis and introduction to other multivariate methods.
** General Text
Dytham, Calvin. (2003 (2005 prin) Choosing and using statistics :a biologist's guide
Hawkins, Dawn. (2005.) Biomeasurement :Dawn Hawkins.
Oxford University Press 0199265151
Jones, Allan (Dec. 1999) Practical Skills in Environmental Science
Prentice Hall 058232873X
Quinn, G. P. (2002.) Experimental design and data analysis for biologists
Cambridge University Press 0521811287
** Recommended Text
Holmes, D., Moody, P. & Dine, D (2006) Research Methods in the Biosciences
Oxford University Press 0199276927
This module is at CQFW Level 7