Verlag: O'Reilly Media (edition 1), 2013
ISBN 10: 1449357105 ISBN 13: 9781449357108
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less 1.48.
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In den WarenkorbPaperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Verlag: O'Reilly Media, Incorporated, 2013
ISBN 10: 1449357105 ISBN 13: 9781449357108
Sprache: Englisch
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In den WarenkorbZustand: Very Good. Used book that is in excellent condition. May show signs of wear or have minor defects.
Verlag: O'Reilly Media (edition 1), 2013
ISBN 10: 1449357105 ISBN 13: 9781449357108
Sprache: Englisch
Anbieter: BooksRun, Philadelphia, PA, USA
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In den WarenkorbPaperback. Zustand: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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In den Warenkorbpaperback. Zustand: Sehr gut. 396 Seiten; 9781449357108.2 Gewicht in Gramm: 1.
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware - Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code.