Biostatistical Design and Analysis Using R (Paperback)
Dr Murray Logan
Sold by Grand Eagle Retail, Mason, OH, U.S.A.
AbeBooks Seller since 12 October 2005
New - Soft cover
Condition: New
Quantity: 1 available
Add to basketSold by Grand Eagle Retail, Mason, OH, U.S.A.
AbeBooks Seller since 12 October 2005
Condition: New
Quantity: 1 available
Add to basketPaperback. 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. First book specifically aimed at biologists/ecologists thatexplains how the new freeware statistical package R can be applied to their problems. This software package is becoming increasingly popular as it ispowerful and free. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller Inventory # 9781405190084
Topics covered include:
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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