| Dewey Class |
519.5 |
| Title |
An Introduction to Data Analysis in R ([EBook]) : Hands-on Coding, Data Mining, Visualization and Statistics from Scratch / / by Alfonso Zamora Saiz, Carlos Quesada González, Lluís Hurtado Gil, Diego Mondéjar Ruiz. |
| Author |
Zamora Saiz, Alfonso |
| Added Personal Name |
Quesada González, Carlos |
| Hurtado Gil, Lluís |
| Mondéjar Ruiz, Diego |
| Other name(s) |
SpringerLink (Online service) |
| Edition statement |
1st ed. 2020. |
| Publication |
Cham : : Springer International Publishing : : Imprint: Springer, , 2020. |
| Physical Details |
XV, 276 p. 99 illus., 81 illus. in color. : online resource. |
| Series |
Use R 2197-5736 |
| ISBN |
9783030489977 |
| Summary Note |
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.: |
| Contents note |
Preface -- 1 Introduction -- 2 Introduction to R -- 3 Databases in R -- 4 Visualization -- 5 Data Analysis with R -- R Packages and Funtions. |
| Mode of acces to digital resource |
Digital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format |
| System details note |
- Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
| Internet Site |
https://doi.org/10.1007/978-3-030-48997-7 |
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