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Beginning R 4 : from beginner to pro /

Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data),...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Wiley, Matt (Autor), Wiley, Joshua F. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Berkeley, CA] : Apress, [2020]
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Wiley, Matt,  |e author. 
245 1 0 |a Beginning R 4 :  |b from beginner to pro /  |c Matt Wiley, Joshua F. Wiley. 
264 1 |a [Berkeley, CA] :  |b Apress,  |c [2020] 
300 |a 1 online resource (481 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |2 rdaft  |0 http://rdaregistry.info/termList/fileType/1002 
347 |b PDF 
504 |a Includes bibliographical references and index. 
505 0 |a 1: Installing R -- 2: Installing Packages and Using Libraries -- 3: Data Input and Output -- 4: Working with Data -- 5: Data and Samples -- 6: Descriptive Statistics -- 7: Understanding Probability and Distribution -- 8: Correlation and Regression -- 9: Confidence Intervals -- 10: Hypothesis Testing -- 11: Multiple Regression -- 12: Moderated Regression -- 13: Analysts of Variance -- Bibliography. 
520 |a Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data import settings for text (as well as the statistical methods to model text-based, categorical data). Each chapter starts with a list of learning outcomes and concludes with a summary of any R functions introduced in that chapter, along with exercises to test your new knowledge. The text opens with a hands-on installation of R and CRAN packages for both Windows and macOS. The bulk of the book is an introduction to statistical methods (non-proof-based, applied statistics) that relies heavily on R (and R visualizations) to understand, motivate, and conduct statistical tests and modeling. Beginning R 4 shows the use of R in specific cases such as ANOVA analysis, multiple and moderated regression, data visualization, hypothesis testing, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. You will: Acquire and install R and RStudio Import and export data from multiple file formats Analyze data and generate graphics (including confidence intervals) Interactively conduct hypothesis testing Code multiple and moderated regression solutions. 
588 0 |a Online resource; title from digital title page (viewed on December 21, 2020). 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a R (Computer program language) 
650 0 |a Statistics  |x Data processing. 
650 6 |a R (Langage de programmation) 
650 6 |a Statistique  |x Informatique. 
650 7 |a R (Computer program language)  |2 fast 
650 7 |a Statistics  |x Data processing  |2 fast 
700 1 |a Wiley, Joshua F.,  |e author. 
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