An Introduction to Data Analysis in R von Alfonso Zamora Saiz | Hands-on Coding, Data Mining, Visualization and Statistics from Scratch | ISBN 9783030489960

An Introduction to Data Analysis in R

Hands-on Coding, Data Mining, Visualization and Statistics from Scratch

von Alfonso Zamora Saiz, Carlos Quesada González, Lluís Hurtado Gil und Diego Mondéjar Ruiz
Mitwirkende
Autor / AutorinAlfonso Zamora Saiz
Autor / AutorinCarlos Quesada González
Autor / AutorinLluís Hurtado Gil
Autor / AutorinDiego Mondéjar Ruiz
Buchcover An Introduction to Data Analysis in R | Alfonso Zamora Saiz | EAN 9783030489960 | ISBN 3-030-48996-5 | ISBN 978-3-030-48996-0

“It was very interesting to go through the pages of this book. The authors should be commended for writing a thorough book about complex concepts of data analysis in R that could, however, be read easily. I warmly recommend this book to students of statistics but also to professionals who would like to acquire advanced analytical skills or improve their competencies in R, especially nowadays with R very popular amongst data analysts.” (Georgios Nikolopoulos, ISCB News, iscb. info, Issue 71, June, 2021)

An Introduction to Data Analysis in R

Hands-on Coding, Data Mining, Visualization and Statistics from Scratch

von Alfonso Zamora Saiz, Carlos Quesada González, Lluís Hurtado Gil und Diego Mondéjar Ruiz
Mitwirkende
Autor / AutorinAlfonso Zamora Saiz
Autor / AutorinCarlos Quesada González
Autor / AutorinLluís Hurtado Gil
Autor / AutorinDiego Mondéjar Ruiz

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.