EBOOK
About
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.
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.