This course consists of three 3-hour webinar sessions (including discussion activities utilising the group chat function, polls, individual activities and breaks). Session one will cover: • Understanding, identifying, minimising variation and its impact. • How the scientific question and experimental design influence the choice of statistical analysis method. • What summary statistics are available and when to use them. • Why and how to transform your data, plus strategies for dealing with outliers. • The structure of a significance test using a two-sample t-test as an example. Session two will cover: • What measures of precision should be used and when, including SD Vs SEM plus confidence interval. • Non-parametric statistical tests and other simple tests to compare more complex data sets. • Basics of ANOVA and why it should often be used instead of multiple t-tests. Session three will cover: • What experimental designs and data features require an extension to statistical analysis methods such as ANOVA and how to incorporate them. • ANOVA for randomised block designs and factorial treatment structures • Analysis of Covariance, ANCOVA Vs Change from Baseline. • Assumptions of ANOVA and ANCOVA