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Autor(en): 
  • Ramalingam Shanmugam
  • Rajan Chattamvelli
  • Descriptive Statistics for Scientists and Engineers: Applications in R 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Juni 2023  
    Genre:  Naturwissensch., Medizin, Technik 
     
    CoefficientofVariation / DataScience / Datenbanken / Datenmanagement / EngineeringStatistics / L-kurtosis / Mathematik für Ingenieure / MultivariateKurtosis / RecursiveAlgorithmforVariance
    ISBN:  9783031323294 
    EAN-Code: 
    9783031323294 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 246 mm / B 173 mm / D 14 mm 
    Gewicht:  430 gr 
    Seiten:  144 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book introduces descriptive statistics and covers a broad range of topics of interest to students and researchers in various applied science disciplines. This includes measures of location, spread, skewness, and kurtosis; absolute and relative measures; and classification of spread, skewness, and kurtosis measures, L-moment based measures, van Zwet ordering of kurtosis, and multivariate kurtosis. Several novel topics are discussed including the recursive algorithm for sample variance; simplification of complicated summation expressions; updating formulas for sample geometric, harmonic and weighted means; divide-and-conquer algorithms for sample variance and covariance; L-skewness; spectral kurtosis, etc. A large number of exercises are included in each chapter that are drawn from various engineering fields along with examples that are illustrated using the R programming language. Basic concepts are introduced before moving on to computational aspects. Some applicationsin bioinformatics, finance, metallurgy, pharmacokinetics (PK), solid mechanics, and signal processing are briefly discussed. Every analyst who works with numeric data will find the discussion very illuminating and easy to follow.

      



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