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 provide 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 modeling techniques

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