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, graphingexploratory data analysis and graphical summariesregression (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.The book is accompanied by a companion website with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.

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