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[null,"1.","Record Nr.",null,"UNISA996418263503316"]
[null,null,"Autore",null,"Zamora Saiz Alfonso"]
[null,null,"Titolo",null,"An Introduction to Data Analysis in R [[electronic resource] ] : Hands-on Coding, Data Mining, Visualization and Statistics from Scratch / / by Alfonso Zamora Saiz, Carlos Quesada González, Lluís Hurtado Gil, Diego Mondéjar Ruiz"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020"]
[null,null,"ISBN",null,"3-030-48997-3"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XV, 276 p. 99 illus., 81 illus. in color.)"]
[null,null,"Collana",null,"Use R!, , 2197-5736"]
[null,null,"Disciplina",null,"519.5"]
[null,null,"Soggetti",null,"Statistics "]
[{"$nulls":4},"Big data"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"R (Computer program language)"]
[{"$nulls":4},"Statistics and Computing/Statistics Programs"]
[{"$nulls":4},"Big Data/Analytics"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Statistics for Business, Management, Economics, Finance, Insurance"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Preface -- 1 Introduction -- 2 Introduction to R -- 3 Databases in R -- 4 Visualization -- 5 Data Analysis with R -- R Packages and Funtions."]
[null,null,null,"Sommario/riassunto","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."]