R - the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment so as to pre a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a

complete practical guide to designing and analyzing real biological research.

Topics covered include

- simple hypothesis testing, graphing,

- exploratory data analysis and graphical summaries

- regression (linear, multi, and non-linear)

- simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot, and repeated measures)

- frequency analysis and generalized linear models

Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modelling techniques.