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[null,"1.","Record Nr.",null,"UNINA9910427048803321"]
[null,null,"Autore",null,"Wiley Matt"]
[null,null,"Titolo",null,"Beginning R 4 : From Beginner to Pro / / by Matt Wiley, Joshua F. Wiley"]
[null,null,"Pubbl/distr/stampa",null,"Berkeley, CA : , : Apress : , : Imprint : Apress, , 2020"]
[null,null,"ISBN",null,"1-4842-6053-8"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XX, 467 p. 110 illus., 66 illus. in color.)"]
[null,null,"Disciplina",null,"005.262"]
[null,null,"Soggetti",null,"Compilers (Computer programs)"]
[{"$nulls":4},"Computer programming"]
[{"$nulls":4},"Computer science - Mathematics"]
[{"$nulls":4},"Mathematical statistics"]
[{"$nulls":4},"Compilers and Interpreters"]
[{"$nulls":4},"Programming Techniques"]
[{"$nulls":4},"Probability and Statistics in Computer Science"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"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."]
[null,null,null,"Sommario/riassunto","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 "]
[{"$nulls":4},"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."]