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Autor(en): 
  • Burt Holland
  • Richard M. Heiberger
  • Statistical Analysis and Data Display: An Intermediate Course with Examples in R 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Dezember 2015  
    Genre:  Schulbücher 
     
    B / Mathematical & statistical software / Mathematical and statistical software / Mathematics and Statistics / Mathematische und statistische Software / Probability & statistics / Shiny / Statistical Theory and Methods
    ISBN:  9781493921218 
    EAN-Code: 
    9781493921218 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Springer Texts in Statistics  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  16754 gr 
    Seiten:  898 
    Illustration:  XXXI, 898 p. 341 illus., 326 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This contemporary presentation of statistical methods features

    extensive use of graphical displays for exploring data and for

    displaying the analysis. 燭he authors demonstrate how to analyze

    data-showing code, graphics, and accompanying tabular listings-for

    all the methods they cover. They emphasize how to construct and

    interpret graphs. They discuss principles of graphical design. They

    identify situations where visual impressions from graphs may need

    confirmation from traditional tabular results. All chapters have

    exercises.


    The authors provide and discuss R functions for all the new graphical

    display formats. All graphs and tabular output in the book were

    constructed using these functions. Complete R scripts for all examples

    and figures are provided for readers to use as models for their own

    analyses.


    This book can serve as a standalone text for statistics majors at the

    master's level and for other quantitatively oriented disciplines at

    the doctoral level, and as a reference book for researchers. In-depth

    discussions of regression analysis, analysis of variance, and design

    of experiments are followed by introductions to analysis of discrete

    bivariate data, nonparametrics, logistic regression, and ARIMA time

    series modeling. The authors illustrate classical concepts and

    techniques with a variety of case studies using both newer graphical

    tools and traditional tabular displays.


    The Second Edition features graphs that are completely redrawn using

    the more powerful graphics infrastructure provided by R's lattice

    package. There are new sections in several of the chapters, revised

    sections in all chapters and several completely new appendices.


    New graphical material includes:

    . an expanded chapter on graphics;

    . a section on graphing Likert Scale Data to build on the importance of

    rating scales in fields from population studies to psychometrics;

    . a discussion on design of graphics that will work for readers with

    color-deficient vision;

    . an expanded discussion on the design of multi-panel graphics;

    . expanded and new sections in the discrete bivariate statistics chapter

    on the use of mosaic plots for contingency tables including the n󫎾

    tables for which the Mantel-Haenszel-Cochran test is appropriate;

    . an interactive (using the shiny package) presentation of the graphics

    for the normal and t-tables that is introduced early and used in many

    chapters.


    The new appendices include discussions of R, the HH package

    designed for R (the material in the HH package was distributed as a

    set of standalone functions with the First Edition of this book), the

    R Commander package, the RExcel system, the shiny package, and a

    minimal discussion on writing R packages. There is a new appendix on

    computational precision illustrating and explaining the FAQ

    (Frequently Asked Questions) about the differences between the

    familiar real number system and the less-familiar floating point

    system used in computers. The probability distributions appendix has

    been expanded to include more distributions (all the distributions in

    base R) and to include graphs of each. The editing appendix from the

    First Edition has been split into four expanded appendices-on working

    style, writing style, use of a powerful editor, and use of LaTeX for

    document preparation.

      



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