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Autor(en): 
  • Larry Pace
  • Beginning R: An Introduction to Statistical Programming 
     

    (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:  Oktober 2012  
    Genre:  EDV / Informatik 
     
    B / Compilers & interpreters / Computer software / Mathematical & statistical software / Mathematical Software / Professional and Applied Computing / Programming languages (Electronic computers) / Programming Languages, Compilers, Interpreters
    ISBN:  9781430245544 
    EAN-Code: 
    9781430245544 
    Verlag:  Apress 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 238 mm / B 192 mm / D 25 mm 
    Gewicht:  590 gr 
    Seiten:  336 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics.

    R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research.

    • Covers the freely-available R language for statistics
    • Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more
    • Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done

      
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