The R BookJohn Wiley & Sons, 7 de nov. de 2012 - 1080 páginas Hugely successful and popular text presenting an extensive and comprehensive guide for all R users The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research. This edition:
Praise for the first edition: ‘...if you are an R user or wannabe R user, this text is the one that should be on your shelf. The breadth of topics covered is unsurpassed when it comes to texts on data analysis in R.’ (The American Statistician, August 2008) ‘The High-level software language of R is setting standards in quantitative analysis. And now anybody can get to grips with it thanks to The R Book...’ (Professional Pensions, July 2007) |
Conteúdo
3 | |
12 | |
Data Input | 137 |
Dataframes | 159 |
Graphics | 189 |
Tables | 244 |
Mathematics | 258 |
Classical Tests | 344 |
Binary Response Variables | 650 |
Generalized Additive Models | 666 |
MixedEffects Models | 681 |
NonLinear Regression | 715 |
MetaAnalysis | 740 |
Bayesian Statistics | 752 |
Tree Models | 768 |
Time Series Analysis | 785 |
Statistical Modelling | 388 |
Regression | 449 |
Analysis of Variance | 498 |
Analysis of Covariance | 537 |
Generalized Linear Models | 557 |
Count Data | 579 |
Count Data in Tables | 599 |
Proportion Data | 628 |
Multivariate Statistics | 809 |
Spatial Statistics | 825 |
Survival Analysis | 869 |
Simulation Models | 893 |
Changing the Look of Graphics | 907 |
References and Further Reading | 971 |
977 | |
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Termos e frases comuns
analysis argument axis bars binomial BOOK calculate called Chapter character Coefficients colour column compute containing continuous contrasts correlation count create dataframe default degrees of freedom density deviance distribution effects equal error Estimate example expected explanatory variables factor levels FALSE female formula four function given gives graph graphics Grassland hypothesis important increases individuals interaction Intercept interval labels length levels linear look male matrix mean measure multiple names negative normal Note null object observed package parameter plot population probability produce proportion random regression residuals response variable rows sample scale separate shows significant single slope spatial species specify squares standard error statistical subscripts treatment tree TRUE values variance vector weight write zero