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.
The book is accompanied by a companion website
www.wiley.com/go/logan/r 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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