Introductory Statistics with RR is an Open Source implementation of the wellknown S language. It works on multiple computing platforms and can be freely downloaded. R is thus ideally suited for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementarylevel introduction to R, targeting both nonstatistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one and twosample tests with continuous data, regression analysis, one and twoway analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis. Peter Dalgaard is associate professor at the Biostatistical Department at the University of Copenhagen and has extensive experience in teaching within the PhD curriculum at the Faculty of Health Sciences. He was chairman of the Danish Society for Theoretical Statistics from 1996 to 2000. Peter Dalgaard has been a key member of the R Core Team since August 1997 and is well known among R users for his activity on the R mailing lists. 
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LibraryThing Review
User Review  pmorrison  LibraryThingI found this a helpful guide in using R to analyze and present data for a paper I was writing. I stopped reading when the paper was submitted, and I don't have anything else to compare it against, but if you need to use R to some end, I'd recommend it. Read full review
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Tästä kirjasta on ilmestynyt 2. painos 2008
Contents
II  1 
IV  3 
VI  4 
VII  6 
VIII  7 
IX  10 
XII  12 
XIII  13 
LXXXV  99 
LXXXVI  103 
LXXXVII  106 
LXXXIX  109 
XCI  110 
XCII  111 
XCIV  115 
XCV  117 
XV  14 
XVI  16 
XVII  17 
XVIII  18 
XIX  19 
XX  20 
XXI  21 
XXII  22 
XXIII  23 
XXIV  24 
XXV  26 
XXVI  27 
XXVIII  29 
XXIX  30 
XXXI  32 
XXXIII  34 
XXXV  36 
XXXVI  37 
XXXVIII  38 
XXXIX  39 
XLI  42 
XLII  43 
XLIII  44 
XLIV  45 
XLVI  46 
XLVII  47 
XLVIII  48 
XLIX  49 
LI  52 
LII  53 
LIII  54 
LIV  55 
LV  57 
LVII  61 
LVIII  63 
LIX  64 
LX  65 
LXII  67 
LXIV  69 
LXV  70 
LXVI  72 
LXVIII  74 
LXIX  75 
LXXI  78 
LXXIII  79 
LXXIV  81 
LXXVI  85 
LXXVII  86 
LXXVIII  89 
LXXX  90 
LXXXI  92 
LXXXII  93 
LXXXIII  95 
XCVI  118 
XCVII  120 
XCIX  121 
C  124 
CII  126 
CIII  129 
CV  131 
CVI  133 
CVII  135 
CVIII  138 
CIX  139 
CXI  140 
CXII  142 
CXIV  143 
CXVI  145 
CXVII  146 
CXIX  149 
CXXI  151 
CXXII  154 
CXXIII  157 
CXXIV  159 
CXXV  160 
CXXVI  162 
CXXVII  164 
CXXVIII  166 
CXXIX  170 
CXXX  171 
CXXXI  172 
CXXXII  173 
CXXXIII  177 
CXXXIV  182 
CXXXV  188 
CXXXVI  191 
CXXXVII  192 
CXXXVIII  193 
CXXXIX  197 
CXL  199 
CXLI  201 
CXLII  203 
CXLIII  204 
CXLIV  208 
CXLV  211 
CXLVII  212 
CXLVIII  213 
CXLIX  216 
CL  218 
CLI  220 
CLII  221 
CLIII  225 
CLIV  247 
261  
Common terms and phrases
alternative hypothesis analysis of variance ANOVA ANOVA table approximate argument binomial distribution blood.glucose calculate cell compute confidence interval contains the following correlation curve data frame contains data set default degrees of freedom described deviance Df Sum Sq difference Error t value Estimate Std example F test Fstatistic factor with levels Figure fitted values folate following columns Format This data function glucose graphics histogram intake Intercept juul linear models logical logistic regression matrix Mean Sq F menarche method missing values model formula names normal distribution Notice null obese observations obtained onesample output pvalue package parameter plot probability prop proportions QQ plot quantiles RSquared regression analysis regression coefficients result rows SPLUS sample estimates Section short.velocity Signif significant slope specify Sq F value Sq Mean Sq standard deviation sum of squares Sum Sq Mean tanner Tanner stage thuesen twosample value Pr(>t variable Variance Table Response weight Wilcoxon zero