Module BO4104: Data Analysis
| Co-ordinator: | Professor Stephen Waldren |
|---|---|
| Course Type: | Mandatory |
| Assessment: | 100% Continual Assessment |
| ECTS: | 5 credits |
| Prerequisites: | None |
Contact hours:
| Lectures: | 18 hours |
|---|---|
| Practicals: | 33 hours |
| Assessments: | |
| Total | 51 hours |
Description:
This module will develop hypothesis testing with a revision of t-tests and explore general linear models, using ANOVA, product-moment correlation and regression. Experimental design will also be covered using ANOVA examples. Equivalent non-parametric approaches will be described. The module will go on to cover chisquared and goodness of fit, and end with a brief introduction to multivariate statistics with a focus on ordination and classification. The module will be delivered by lectures, demonstration and discussion sessions, and by hands on use of various software packages.
Learning outcomes:
On successful completion of this module students should be able to:
- Design experiments effectively
- Describe how various processes contribute to data variation
- Use statistical software packages to analyse experimental data effectively
- Apply commonly used statistical tests with discrimination and use these tests to draw valid conclusions from data
- Present data in effective formats
- Critically interpret and appraise commonly used methods of data analysis published in scientific literature.