An Introduction to Data Analysis in R

• Verfasst von: Zamora Saiz, Alfonso [VerfasserIn]
• Verfasst von: Quesada González, Carlos [VerfasserIn]
• Verfasst von: Hurtado Gil, Lluís [VerfasserIn]
• Verfasst von: Mondéjar Ruiz, Diego [VerfasserIn]
• Titel: An Introduction to Data Analysis in R
• Titelzusatz: Hands-on Coding, Data Mining, Visualization and Statistics from Scratch
• Verf.angabe: by Alfonso Zamora Saiz, Carlos Quesada González, Lluís Hurtado Gil, Diego Mondéjar Ruiz
• Ausgabe: 1st ed. 2020.
• Verlagsort: Cham
• Verlagsort: Cham
• Verlag: Springer International Publishing
• Verlag: Imprint: Springer
• E-Jahr: 2020
• Jahr: 2020.
• Jahr: 2020.
• Umfang: 1 Online-Ressource(XV, 276 p. 99 illus., 81 illus. in color.)
• Gesamttitel/Reihe: Use R!
• Gesamttitel/Reihe: Springer eBook Collection
• ISBN: 978-3-030-48997-7
• DOI: doi:10.1007/978-3-030-48997-7
• Schlagwörter: (s)Datenanalyse / (s)R <Programm>
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe: Zamora Saiz, Alfonso: An introduction to data analysis in R. - Cham, Switzerland : Springer, 2020. - xv, 276 Seiten
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe
• RVK-Notation: ST 601
• K10plus-PPN: 1726031179
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

Preface -- 1 Introduction -- 2 Introduction to R -- 3 Databases in R -- 4 Visualization -- 5 Data Analysis with R -- R Packages and Funtions.

Abstract

This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.