000 06857cam a2201009 i 4500
001 ocn809365744
003 OCoLC
005 20171224114043.0
006 m o d
007 cr |||||||||||
008 120905s2013 enk ob 001 0 eng
010 _a 2012036181
040 _aDLC
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019 _a827207730
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020 _a9781118448960
_q(ePub)
020 _a1118448960
_q(ePub)
020 _a9781118448946
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020 _a1118448944
_q(Adobe PDF)
020 _a9781118448922
_q(mobiPocket)
020 _a1118448928
_q(mobiPocket)
020 _a9781118448908
_q(electronic bk.)
020 _a1118448901
_q(electronic bk.)
020 _z9780470973929
_q(hardback)
020 _z0470973927
020 _z9781299190283
020 _z1299190286
029 1 _aAU@
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035 _a(OCoLC)809365744
_z(OCoLC)827207730
_z(OCoLC)828617949
_z(OCoLC)841325769
_z(OCoLC)860794453
037 _a450278
_bMIL
037 _a98842DE4-BC95-42AB-8830-CD22369C7BE2
_bOverDrive, Inc.
_nhttp://www.overdrive.com
042 _apcc
050 0 0 _aQA276.45.R3
072 7 _aMAT
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072 7 _aMAT
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082 0 0 _a519.50285/5133
_223
084 _aMAT029000
_2bisacsh
049 _aMAIN
100 1 _aCrawley, Michael J.
245 1 4 _aThe R book /
_cMichael J. Crawley.
250 _aSecond edition.
264 1 _aChichester, West Sussex, UK :
_bWiley,
_c2013.
300 _a1 online resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
520 _a"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: Features full colour text and extensive graphics throughout. Introduces a clear structure with numbered section headings to help readers locate information more efficiently. Looks at the evolution of R over the past five years. Features a new chapter on Bayesian Analysis and Meta-Analysis. Presents a fully revised and updated bibliography and reference section. Is supported by an accompanying website allowing examples from the text to be run by the user. 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) "--
_cProvided by publisher.
520 _a"This edition introduces the advantages of the R environment, in a user-friendly format, to beginners and intermediate users in a range of disciplines, from science and engineering to medicine and economics"--
_cProvided by publisher.
504 _aIncludes bibliographical references and index.
500 _aMachine generated contents note: Preface vii 1 Getting Started 1 2 Essentials of the R Language 9 3 Data Input 97 4 Dataframes 107 5 Graphics 135 6 Tables 183 7 Mathematics 195 8 Classical Tests 279 9 Statistical Modelling 323 10 Regression 387 11 Analysis of Variance 449 12 Analysis of Covariance 489 13 Generalized Linear Models 511 14 Count Data 527 15 Count Data in Tables 549 16 Proportion Data 569 17 Binary Response Variables 593 18 Generalized Additive Models 611 19 Mixed-Effects Models 627 20 Non-linear Regression 661 21 Meta-analysis xxx 22 Bayesian statistics xxx 23 Tree Models 685 24 Time Series Analysis 701 25 Multivariate Statistics 731 26 Spatial Statistics 749 27 Survival Analysis 787 28 Simulation Models 811 29 Changing the Look of Graphics 827 References and Further Reading 873 Index 877s.
588 0 _aPrint version record and CIP data provided by publisher.
505 0 _aPreface -- 1. Getting Started -- 2. Essentials of the R Language -- 3. Data Input -- 4. Dataframes -- 5. Graphics -- 6 Tables -- 7. Mathematics -- 8. Classical Tests -- 9. Statistical Modelling -- 10. Regression -- 11. Analysis of Variance -- 12. Analysis of Covariance -- 13. Generalized Linear Models -- 14. Count Data -- 15. Count Data in Tables -- 16. Proportion Data -- 17. Binary Response Variables -- 18. Generalized Additive Models -- 19. Mixed-Effects Models -- 20. Non-linear Regression -- 21. Meta-analysis -- 22. Bayesian statistics -- 23. Tree Models -- 24. Time Series Analysis -- 25. Multivariate Statistics -- 26. Spatial Statistics -- 27. Survival Analysis -- 28. Simulation Models -- 29. Changing the Look of Graphics.
650 0 _aR (Computer program language)
650 0 _aMathematical statistics
_xData processing.
650 4 _aR (Computer program language)
650 4 _aMathematical statistics
_xData processing.
650 4 _aMATHEMATICS
_xProbability & Statistics
_xGeneral.
650 7 _aMATHEMATICS
_xProbability & Statistics
_xGeneral.
_2bisacsh
650 7 _aMathematical statistics
_xData processing.
_2fast
_0(OCoLC)fst01012133
650 7 _aR (Computer program language)
_2fast
_0(OCoLC)fst01086207
650 7 _aDatorprogram.
_2sao
650 7 _aMatematisk statistik.
_2sao
650 7 _aDatabehandling.
_2sao
650 7 _aR (programspråk)
_2sao
650 7 _aR (Computer program language)
_2local
650 7 _aMathematical statistics / Data processing.
_2local
655 4 _aElectronic books.
776 0 8 _iPrint version:
_aCrawley, Michael J.
_tR book.
_b2e.
_z9780470973929
_w(DLC) 2012027339
856 4 0 _uhttp://onlinelibrary.wiley.com/book/10.1002/9781118448908
_zWiley Online Library
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