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Autor(en): 
  • Pierre Lafaye de Micheaux
  • Rémy Drouilhet
  • Benoit Liquet
  • The R Software: Fundamentals of Programming and Statistical Analysis 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  Februar 2014  
    Genre:  Schulbücher 
     
    Algebra / Compiler / Compiler und Übersetzer / COMPUTERS / Mathematical & Statistical Software / COMPUTERS / Programming Languages / General / Datenverarbeitung / Anwendungen / Mathematik, Statistik / MATHEMATICS / Probability & Statistics / General / Mathematik / Statistik / Mathematische und statistische Software / Naturwissenschaften, allgemein / Programmier- und Skriptsprachen, allgemein / Programmiersprachen / Statistik / Stochastik / Übersetzer (EDV) / Wahrscheinlichkeitsrechnung
    ISBN:  9781461490197 
    EAN-Code: 
    9781461490197 
    Verlag:  Springer New York 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Statistics and Computing  
    Dimensionen:  H 241 mm / B 160 mm / D 39 mm 
    Gewicht:  1277 gr 
    Seiten:  668 
    Zus. Info:  HC runder Rücken kaschiert 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance.  The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included arematrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

      
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