Cover Image

An Introduction to Data Analysis in R : Hands-on Coding, Data Mining, Visualization and Statistics from Scratch /

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...

Full description

Bibliographic Details
Main Authors:	Zamora Saiz, Alfonso (Author), Quesada González, Carlos (Author), Hurtado Gil, Lluís (Author), Mondéjar Ruiz, Diego (Author)
Corporate Author:	SpringerLink (Online service)
Format:	eBook
Language:	English
Published:	Cham : Springer International Publishing : Imprint: Springer, 2020.
Edition:	1st ed. 2020.
Series:	Use R!,
Subjects:	Statistics . Big data. Data mining. Statistics and Computing/Statistics Programs. Big Data/Analytics. Data Mining and Knowledge Discovery. Statistics for Business, Management, Economics, Finance, Insurance. Electronic books.
Online Access:	Connect to the full text of this electronic book

Similar Items

Computational and Methodological Statistics and Biostatistics : Contemporary Essays in Advancement /
Published: (2020)

Statistical Modeling in Biomedical Research : Contemporary Topics and Voices in the Field /
Published: (2020)

Analyzing Dependent Data with Vine Copulas : A Practical Guide With R /
by: Czado, Claudia
Published: (2019)

Macroeconomic Forecasting in the Era of Big Data : Theory and Practice /
Published: (2020)

Innovations in Big Data Mining and Embedded Knowledge /
Published: (2019)

Intelligent Methods and Big Data in Industrial Applications /
Published: (2019)

Applying Data Science : How to Create Value with Artificial Intelligence /
by: Kordon, Arthur K.
Published: (2020)

Contemporary Experimental Design, Multivariate Analysis and Data Mining : Festschrift in Honour of Professor Kai-Tai Fang /
Published: (2020)

Statistics for Data Science and Policy Analysis /
Published: (2020)

Practical Text Analytics : Maximizing the Value of Text Data /
by: Anandarajan, Murugan, et al.
Published: (2019)

Data Mining with SPSS Modeler : Theory, Exercises and Solutions /
by: Wendler, Tilo, et al.
Published: (2021)

Data Analysis and Classification : Methods and Applications /
Published: (2021)

Data Science and Big Data Analytics : ACM-WIR 2018 /
Published: (2019)

Statistics for Health Data Science : An Organic Approach /
by: Etzioni, Ruth, et al.
Published: (2020)

Classification and Data Analysis : Theory and Applications /
Published: (2020)

R For Marketing Research and Analytics /
by: Chapman, Chris, et al.
Published: (2019)

Essentials of Business Analytics : An Introduction to the Methodology and its Applications /
Published: (2019)

Statistical Analysis of Microbiome Data /
Published: (2021)

An Introduction to Machine Learning /
by: Kubat, Miroslav
Published: (2021)

Fundamentals of High-Dimensional Statistics : With Exercises and R Labs /
by: Lederer, Johannes
Published: (2022)

Machine Learning and Artificial Intelligence /
by: Joshi, Ameet V.
Published: (2020)

Machine Learning Foundations : Supervised, Unsupervised, and Advanced Learning /
by: Jo, Taeho
Published: (2021)

An Introduction to Sequential Monte Carlo /
by: Chopin, Nicolas, et al.
Published: (2020)

Data Science for Economics and Finance : Methodologies and Applications /
Published: (2021)

Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R : A Workbook /
by: Hair Jr., Joseph F., et al.
Published: (2021)

An Introduction to Bayesian Inference, Methods and Computation /
by: Heard, Nick
Published: (2021)

Entertainment Science : Data Analytics and Practical Theory for Movies, Games, Books, and Music /
by: Hennig-Thurau, Thorsten, et al.
Published: (2019)

A Concise Guide to Market Research : The Process, Data, and Methods Using IBM SPSS Statistics /
by: Sarstedt, Marko, et al.
Published: (2019)

Data Privacy and Trust in Cloud Computing : Building trust in the cloud through assurance and accountability /
Published: (2021)

Computational Intelligence for Business Analytics /
Published: (2021)

Python for Marketing Research and Analytics /
by: Schwarz, Jason S., et al.
Published: (2020)

How Algorithms Create and Prevent Fake News : Exploring the Impacts of Social Media, Deepfakes, GPT-3, and More /
by: Giansiracusa, Noah
Published: (2021)

Introduction to Data Systems : Building from Python /
by: Bressoud, Thomas, et al.
Published: (2020)

Big Data, Big Challenges: A Healthcare Perspective : Background, Issues, Solutions and Research Directions /
Published: (2019)

Data Analytics and Learning : Proceedings of DAL 2018 /
Published: (2019)

Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics : Theories and Applications /
Published: (2021)

Time Series Analysis for the State-Space Model with R/Stan /
by: Hagiwara, Junichiro
Published: (2021)

Industry 4.0 for SMEs : Challenges, Opportunities and Requirements /
Published: (2020)

Data Engineering and Intelligent Computing : Proceedings of ICICC 2020 /
Published: (2021)

Big Data Platforms and Applications : Case Studies, Methods, Techniques, and Performance Evaluation /
Published: (2021)