|| RSM0810 |
|| STATISTICS FOR EXPERIMENTAL SCIENTISTS |
|| 2004/2005 |
|| Dr Malcolm H Leitch |
|| Semester 2 (Taught over 2 semesters) |
|| Miss Sylvia G Lutkins |
| Course delivery
|| Lecture || 36 Hours 18 x 2 hour combined lectures/practical sessions |
|| Practical || 12 Hours 6 x 2 hour computer workshops |
|Assessment Type||Assessment Length/Details||Proportion|
|Semester Exam||3 Hours Open book written examination Outcomes assessed 1, 2, 3||30%|
|Semester Assessment|| Continuous assessment Outcomes assessed: 1, 2, 3, 4 ||30%|
|Semester Assessment|| Assignment Outcomes assessed: 1, 2, 3 ||40%|
|Supplementary Assessment|| data analysis assignment outcomes 1, 2, 3, 4 ||100%|
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.
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.
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.
.1 Independent project work
Students are required to collect, analyse and interpret data for the assignment.
.2 IT and information handling
Students will use statistical packages to analyse data.
.3 Use and analysis of numerial information
The prime basis of the module
.4 Writing in an academic context
Required for the assignment
.7 Self management
For the assignment project, students will need to be responsible for organising their own time management
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
Daniel, W W (1995) Biostatistics: A foundation for Analyses in the Health Sciences
6th. Wiley, New York
Gill, L (1978) Design and analysis of experiments in the animal and medical sciences 3 vols.
State University Press, Iowa
This module is at CQFW Level 7