Module Information

Module Identifier
Module Title
Academic Year
Semester 1
Other Staff

Course Delivery

Delivery Type Delivery length / details
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 Outcomes

On 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
  • Multivariate Methods
  • Use of PCA/DFA/PLS analysis and introduction to other multivariate methods.

Reading List

General Text
Dytham, Calvin. (2003 (2005 prin) Choosing and using statistics :a biologist's guide Primo search Hawkins, Dawn. (2005.) Biomeasurement :Dawn Hawkins. Oxford University Press Primo search Jones, Allan (Dec. 1999) Practical Skills in Environmental Science Prentice Hall Primo search Quinn, G. P. (2002.) Experimental design and data analysis for biologists Cambridge University Press Primo search
Recommended Text
Holmes, D., Moody, P. & Dine, D (2006) Research Methods in the Biosciences Oxford University Press Primo search


This module is at CQFW Level 7