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Autor(en): 
  • John Jobson
  • Applied Multivariate Data Analysis: Volume II: Categorical and Multivariate Methods 
     

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


    Übersicht

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    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  März 1994  
    Genre:  Wirtschaft / Recht 
     
    MATHEMATICS / Applied / MATHEMATICS / Probability & Statistics / Multivariate Analysis
    ISBN:  9780387978048 
    EAN-Code: 
    9780387978048 
    Verlag:  Springer Nature B.V. 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Springer Texts in Statistics  
    Dimensionen:  H 234 mm / B 156 mm / D 41 mm 
    Gewicht:  1243 gr 
    Seiten:  768 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    A Second Course in Statistics The past decade has seen a tremendous increase in the use of statistical data analysis and in the availability of both computers and statistical software. Business and government professionals, as well as academic researchers, are now regularly employing techniques that go far beyond the standard two-semester, introductory course in statistics. Even though for this group of users shorl courses in various specialized topics are often available, there is a need to improve the statistics training of future users of statistics while they are still at colleges and universities. In addition, there is a need for a survey reference text for the many practitioners who cannot obtain specialized courses. With the exception of the statistics major, most university students do not have sufficient time in their programs to enroll in a variety of specialized one-semester courses, such as data analysis, linear models, experimental de­ sign, multivariate methods, contingency tables, logistic regression, and so on. There is a need for a second survey course that covers a wide variety of these techniques in an integrated fashion. It is also important that this sec­ ond course combine an overview of theory with an opportunity to practice, including the use of statistical software and the interpretation of results obtained from real däta.

      



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