An essential textbook for any student or researcher in biology needing to design experiments sample programs or analyse the resulting data. The text begins with a revision of estimation & hypothesis testing methods covering both classical & Bayesian philosophies before advancing to the analysis of linear & generalized linear models. Topics covered include linear & logistic regression simple & complex ANOVA models (for factorial nested block split-plot & repeated measures & covariance designs) & log-linear models. Multivariate techniques including classification & ordination are then introduced. Special emphasis is placed on checking assumptions exploratory data analysis & presentation of results. The main analyses are illustrated with many examples from published papers & there is an extensive reference list to both the statistical & biological literature. The book is supported by a web-site that provides all data sets questions for each chapter & links to software.