Module Identifier RS25720  
Academic Year 2003/2004  
Co-ordinator Dr Malcolm H Leitch  
Semester Semester 2 (Taught over 2 semesters)  
Course delivery Lecture   10 Hours 10 x 1 hour lectures on Research Methodologies  
  Lecture   36 Hours 18 x 2 hour combined lectures/practical sessions on data analysis  
  Other   14 Hours 3 x 2 hour workshops in Research Methodologies; 4 x 2 hour workshops in Data Analysis  
Assessment TypeAssessment Length/DetailsProportion
Semester Exam3 Hours Data analysis Open book examination Outcomes assessed: 2, 5, 6, 7  25%
Semester Assessment Research methodologies assignment Outcomes assessed: 1, 3, 4, 7  50%
Semester Assessment Practical exercises Outcomes assessed: 5, 6, 7  25%
Supplementary Exam3 Hours Open book examination  50%
Supplementary Assessment Revised research plan  50%

Learning outcomes

On completion of this module, students should be able to:

1. Produce a fully documented review of a body of scientific/scocial science literature and draw logical conclusions
2. Discuss the differences in experimental approach between quantitative and qualitative research
3. Propose an appropriate experimental hypothesis for subsequent testing
4. Design an appropriate experimental approach for testing an experimental hypothesis
5. Identify appropriate methods of analysis for different types of data
6. Analyse data using a range of statistical methods
7. Interpret experimental data and draw suitable conclusions based on the results of the data analysis

Brief description

The module is designed to develop an appreciation of the scientific method, moving from a critical analysis of the existing scientific literature to the development of an experimental hypothesis through to the design of experimental approaches for testing the hypothesis, and the statistical evaluation of data and their interpretation. The production of a detailed research plan will require students to review the relevant scientific literature, propose an experimental hypothesis for testing, and design an experiment to test this hypothesis, taking due account of statistical techniques to be used for data analysis and resources available. This will adopt a formative approach in which the students will be required to develop their plan in stages, will be provided with feedback on their initial attempts and then be given opportunity to revise their plans.

In addition, the module includes the theory and practice of a range of statistical methodologies. These include probability, a description of the normal distribution and parametric tests based on samples drawn from normally distributed populations including t-tests, one way and multi way ANOVA and correlation and regression analysis. Non-parametric methods will include chi-square analysis of frequencies, contingency tables, Mann-Whitney U test and Spearman rank correlation. This component of the course is taught through a series of two-hour lecture/practical sessions consisting of an introductory lecture followed by practical examples to work through.   

Transferable skills

.1 Independent project work
The production of the detailed research plan will require students to work independently.

.2 IT and information handling
Students will be required to use IT-based literature searches for the production of their research plan and to produce their assignment in word processed format.

.3 Use and analysis of numerical information
Data analysis using a range of statistical methods represents a major component of the module and will be assessed by means of open book examination.

.4 Writing in an academic context
The Literature Review part of the research plan will require students to write in an academic context appropriate to their chosen area of research, as well as to demonstrate an ability to interpret rather than simply reporting existing literature.

.6 Careers need awareness
The skills obtained from this module will be transferable to many real world situations that are likely to confront students in their subsequent careers

.7 Self-management
The production of the research plan will require students to work to specified deadlines, but they will be responsible for organizing their own time management to meet those deadlines

Reading Lists

Mead, R; Curnow, R H & Hasted, A M (1993) Statistical Methods in Agriculture and Experimental Biology 2nd. Chapman and Hall, London
Campbell, R C (1989) Statistics for Biologists 3rd. Cambridge University Press, London


This module is at CQFW Level 5