Basic Elements of Computational Statistics

This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational s...

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Bibliographic Details
Main Authors: Härdle, Wolfgang Karl, Okhrin, Ostap (Author), Okhrin, Yarema (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2017, 2017
Edition:1st ed. 2017
Series:Statistics and Computing
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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260 |a Cham  |b Springer International Publishing  |c 2017, 2017 
300 |a XXI, 305 p. 97 illus., 66 illus. in color  |b online resource 
505 0 |a The Basics of R -- Numerical Techniques -- Combinatorics and Discrete Distributions -- Univariate Distributions -- Univariate Statistical Analysis -- Basic Nonparametric Methods -- Multivariate Distributions -- Multivariate Statistical Analysis -- Random Numbers in R -- Advanced Graphical Techniques in R -- Symbols and Notations 
653 |a Mathematical statistics 
653 |a Statistical Theory and Methods 
653 |a Statistics  
653 |a Biostatistics 
653 |a Statistics and Computing/Statistics Programs 
653 |a Biostatistics 
653 |a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences 
653 |a Probability and Statistics in Computer Science 
653 |a Statistics for Business, Management, Economics, Finance, Insurance 
700 1 |a Okhrin, Ostap  |e [author] 
700 1 |a Okhrin, Yarema  |e [author] 
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520 |a This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R. It covers mathematical, statistical as well as programming problems in computational statistics and contains a wide variety of practical examples. In addition to the numerous R sniplets presented in the text, all computer programs (quantlets) and data sets to the book are available on GitHub and referred to in the book. This enables the reader to fully reproduce as well as modify and adjust all examples to their needs. The book is intended for advanced undergraduate and first-year graduate students as well as for data analysts new to the job who would like a tour of the various statistical tools in a data analysis workshop. The experienced reader with a good knowledge of statistics and programming might skip some sections on univariate models and enjoy the various mathematical roots of multivariate techniques. The Quantlet platform quantlet.de, quantlet.com, quantlet.org is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding Data-Driven Documents-based visualization allows readers to reproduce the tables, pictures and calculations inside this Springer book