This module develops analytical skills required for the final year Honours Project, scientific research in general, and your future career. The major skills are computer literacy and graphical presentation, understanding of scientific method and hypothesis testing, a few simple mathematical concepts, and basic methods of statistical analysis, including non-parametric tests, analysis of variance and data modelling.
Aims and Objectives
Having successfully completed this module you will be able to:
- Draw conclusions from the outputs of statistical analyses.
- Choose the appropriate statistical test for a variety of simple problems, and plan and design experiments before collecting data, taking account of the statistical techniques you will use.
- Perform simple non-parametric and parametric statistical tests of dependency, variance and correlation, using the R environment
- Explain the concepts of the null hypothesis, p-value, statistical power, type I & II errors, significance and non-significance, and draw appropriate conclusions for the hypotheses being tested.
- Use a statistical model in R to make a statement about predicted relationships.
- Calculate the mean, median, mode, standard deviation, standard error, confidence intervals and inter-quartile ranges of a sample.
- Calculate logarithms and other simple transformations and the equation of a straight line.
- Outline the nature of scientific knowledge and the processes of framing and testing hypotheses.
- Explain the difference between parametric and non-parametric statistics, and the assumptions that underlie them.
- Enter data into the open-source R environment, check for errors, write and use R scripts, and plot, label and annotate graphs.
Scientific method and theories, hypothesis testing, biological data, simple data handling and spreadsheets, graphics and report writing, simple statistical tests, non-parametric tests, contingency tests, multivariate methods, one-way and two-way analysis of variance, statistical modelling, regression and correlation, how to plan an analysis and choose an appropriate test.
Learning and Teaching
Teaching and learning methods
Teaching and learning will involve lectures, measurement of biological samples, computer-based practicals.
|Practical classes and workshops||20|
|Total study time||150|
Resources & Reading list
Dytham, C (2011). Choosing and Using Statistices: A Biologist's guide. Blackwell Science.
This is how we’ll formally assess what you have learned in this module.
This is how we’ll assess you if you don’t meet the criteria to pass this module.