Learning Outcomes:
Learning Outcomes:
• Design a biological / environmental experiment, taking due account of independence, allocation of replicates and controls;
• Organise and manipulate data on a computer;
• Fit and validate a statistical model to biological data;
• Test a null-hypothesis using a fitted statistical model;
• Accurately communicate data using graphs, tables and written text;
• Answer research questions and draw strong, defendable conclusions using modern statistical data analysis methods.
Skills:
The module will contribute towards the development of the following skills:
• Effective presentation and writing of technical information
• Transparency and collaboration on data analysis projects
• Spreadsheet (Excel), R statistical language and general computer skills
Indicative Module Content:
1. Getting started with R
2. Data import into R
3. Data organisation
4. Exploratory data analysis
5. Data distributions
6. Sampling a population
7. Statistical modelling
8. General linear models (Fitting)
9. General linear models (Hypothesis testing)
10. Model validation
11. Post-hoc testing
12. Models with multiple factors
13. Linear regression using general linear models
14. Modelling qualitative data (Chi-square tests)