Aims of the module
To develop an appreciation of the role of statistical analysis in the interpretation of experimental data.
To develop skills in the use of a range of commonly used statistical techniques.

Learning outcomes
On completion of this module students will be able to:

i) identify appropriate methods of analysis for different types of data.

ii) demonstrate competence in data analysis using a range of statistical methods.

iii) draw suitable conclusions based on the results of data analysis.

Syllabus / Curriculum design
A practical course with short explanatory lectures. Content will vary to some extent in response to the specific needs of individual courses. Content includes probability, a description of the normal distribution, parametric tests based on samples drawn from normally distributed populations including t-test and one-way and multi-way ANOVA. Correlation and regression. Non-parametric methods will include chi-square analysis of frequencies, contingency tables, Mann-Whitney, Wilcoxon's matched pairs and Spearman Rank correlation. The Binomial, Poisson and negative binomial distributions and associated tests of dispersion will be described