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Description: |
xxviii, 546 pages : illustrations ; 26 cm |
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Bibliography Note: |
Includes bibliographical references (pages 531-533) and index. |
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Contents Note: |
Contents: Introduction to R -- Data sets -- Introductory statistical principles -- Sampling and experimental design with R -- Graphical data presentation -- Simple hypothesis testing, one and two population tests -- Introduction to linear models -- Correlation and simple linear regression -- Multiple and curvilinear regression -- Single factor classification (ANOVA) -- Nested ANOVA -- Factorial ANOVA -- Unreplicated factorial designs, randomized block and simple repeated measures -- Partly nested designs: split plot and complex repeated measures -- Analysis of covariance (ANCOVA) -- Simple frequency analysis -- Generalized linear models (GLM). |
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Restriction Note: |
Online access restricted to licenced organisations. |
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Summary, Etc. Note: |
Summary: 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 inc. |
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Additional Physical Forms: |
Online version: Logan, Murray. Biostatistical design and analysis using R. Chichester, UK ; Hoboken, NJ : Wiley-Blackwell, 2010 (OCoLC)760986035 |
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Index - Uncontrolled: |
R (COMPUTER PROGRAM LANGUAGE) |