Handbook

This is a course in statistics that focuses on the principles of good experimental design and the statistical tools appropriate for discrete valued data. The course is an optional component of a statistics major. Students will learn about the importance experimental design, Analysis of Variance (ANOVA), multiple comparison techniques, randomised complete block designs, Latin square designs, two-way interaction models, factorial designs and their analysis, random effects models, analysis of cross-tabulated data, logistic and Poisson regression for analysis of binary and count data and log-linear models for contingency tables. Students will use the statistical package R/RStudio throughout the course. Lecture content will be delivered in-person and will be recorded and made available online. Tutorials will be face to face.