Module Identifier RSM0810  
Academic Year 2006/2007  
Co-ordinator Dr Malcolm H Leitch  
Semester Semester 2 (Taught over 2 semesters)  
Other staff Miss Sylvia G Lutkins  
Course delivery Lecture   1 x 2 hour lecture per week  
  Practical   6 x 2 hour computer workshops in Semester 1  
Assessment TypeAssessment Length/DetailsProportion
Semester Assessment Continuous assessment Outcomes assessed: 1, 2, 3, 4  30%
Semester Assessment Assignment Outcomes assessed: 1, 2, 3  40%
Semester Exam3 Hours Open book written examination Outcomes assessed 1, 2, 330%
Supplementary Assessment Data analysis assignment outcomes 1, 2, 3, 4  100%

Learning outcomes

On completion of this module students will be able to:

1. Identify appropriate methods of analysis for different types of data.

2. Analyse data using a range of statistical analyses.

3. Interpret the results of data analyses.

4. Apply statistical knowledge in the content of postgraduate reserch.

Brief description

A practical course with short explanatory lectures and practical demonstration. The content will include probability, normal distribution, parametric tests including t-tests, one way and multi way ANOVA. Correlation and regression. Non parametric methods will include chi-square analysis of frequencies, contingency tables, Mann-Whitney U test, Spearman rank correlation. Computer packages will be used in practical/demo sessions to reinforce the lecture material. To some extent the exact course content will vary in response to student ability and need.

Module Outline
NB This module will be taught in two parts:-

Part 1 - Semester 1, is taught joint with undergraduates module RS21810. All the assessment associated with module is compulsory to all students, attendance at lectures/practicals is optional.

Part 2 - Semester 2, is taught exclusively to MSc students. Both assessment and attendance at lectures/practicals is compulsory.

Module Skills

Research skills Students are required to collect, analyse and interpret data for the assignment  
Communication Students are required to present the assignment in an appropriate academic style.  
Improving own Learning and Performance Students need to be capable of organising themselves to ensure the assignment is submitted on time.  
Information Technology Students will be expected to use statistical packages to analyse data.  

Reading Lists

** General Text
Campbell, R C (1989) Statistics for Biologists 3rd. Cambridge University Press, London 0521369320
Daniel, W W (1995) Biostatistics: A foundation for Analyses in the Health Sciences 6th edition. Wiley, New York 0471110833
Gill, L (1978) Design and analysis of experiments in the animal and medical sciences Vol 1s. State University Press, Iowa 0813800109
Gill, L (1978) Design and analysis of experiments in the animal and medical sciences. Vol 2 State University Press, Iowa 0813800609
Gill, L (1978) Design and analysis of experiments in the animal and medical sciences. Vol 3 State University Press, Iowa 0813801109
Mead, R; Curnow, R H & Hasted, A M (1993) Statistical Methods in Agriculture and Experimental Biology 2nd edition. Chapman and Hall, London
Quinn, B P and Feough, M T (2002) Experimental design and data analysis for biologists Cambridge University Press 0521009766


This module is at CQFW Level 7