LEADER 03343nam 2200685Ia 450 001 9910819516303321 005 20210702172430.0 010 $a1-4443-6247-X 010 $a1-282-54792-5 010 $a9786612547928 010 $a1-4443-1962-0 010 $a1-4443-1963-9 035 $a(CKB)2670000000014784 035 $a(EBL)514460 035 $a(OCoLC)609863007 035 $a(SSID)ssj0000357210 035 $a(PQKBManifestationID)11254492 035 $a(PQKBTitleCode)TC0000357210 035 $a(PQKBWorkID)10352144 035 $a(PQKB)10766551 035 $a(MiAaPQ)EBC514460 035 $a(MiAaPQ)EBC4041932 035 $a(Au-PeEL)EBL514460 035 $a(CaPaEBR)ebr10377840 035 $a(CaONFJC)MIL254792 035 $a(Au-PeEL)EBL4041932 035 $a(CaPaEBR)ebr11114672 035 $a(OCoLC)613206391 035 $a(PPN)250326302 035 $a(EXLCZ)992670000000014784 100 $a20100111d2010 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBiostatistical design and analysis using R$b[electronic resource] $ea practical guide /$fMurray Logan 205 $a1st ed. 210 $aHoboken, N.J. $cWiley-Blackwell$d2010 215 $a1 online resource (576 p.) 300 $aDescription based upon print version of record. 311 $a1-4443-3524-3 311 $a1-4051-9008-6 320 $aIncludes bibliographical references and index. 327 $aBiostatistical Design and Analysis Using R; Contents; Preface; R quick reference card; General key to statistical methods; 1 Introduction to R; 2 Datasets; 3 Introductory statistical principles; 4 Sampling and experimental design with R; 5 Graphical data presentation; 6 Simple hypothesis testing - one and two population tests; 7 Introduction to Linear models; 8 Correlation and simple linear regression; 9 Multiple and curvilinear regression; 10 Single factor classification (ANOVA); 11 Nested ANOVA; 12 Factorial ANOVA 327 $a13 Unreplicated factorial designs - randomized block and simple repeated measures14 Partly nested designs: split plot and complex repeated measures; 15 Analysis of covariance (ANCOVA); 16 Simple Frequency Analysis; 17 Generalized linear models (GLM); Bibliography; R index; Statistics index 330 $aR - 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 covere 606 $aBiometry 606 $aR (Computer program language) 615 0$aBiometry. 615 0$aR (Computer program language) 676 $a570.1/5195 700 $aLogan$b Murray$0517065 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910819516303321 996 $aBiostatistical design and analysis using R$9845293 997 $aUNINA