An introduction to data analysis in R : hands-on coding, data mining, visualization and statistics from scratch
Author(s)
Bibliographic Information
An introduction to data analysis in R : hands-on coding, data mining, visualization and statistics from scratch
（Use R! / series editors, Robert Gentleman, Kurt Hornik, Giovanni Parmigiani）
Springer, c2020
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Note
Other authors: Carlos Quesada González, Lluís Hurtado Gil, Diego Mondéjar Ruiz
Includes bibliographical references
Description and Table of Contents
Description
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.
Table of Contents
Preface.- 1 Introduction.- 2 Introduction to R.- 3 Databases in R.- 4 Visualization.- 5 Data Analysis with R.- R Packages and Funtions.
by "Nielsen BookData"
