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Data Analysis with R, Second Edition

You're reading from   Data Analysis with R, Second Edition A comprehensive guide to manipulating, analyzing, and visualizing data in R

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Product type Paperback
Published in Mar 2018
Publisher Packt
ISBN-13 9781788393720
Length 570 pages
Edition 2nd Edition
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Author (1):
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Tony Fischetti Tony Fischetti
Author Profile Icon Tony Fischetti
Tony Fischetti
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Table of Contents (19) Chapters Close

Preface 1. RefresheR FREE CHAPTER 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data To Reason About The World 6. Testing Hypotheses 7. Bayesian Methods 8. The Bootstrap 9. Predicting Continuous Variables 10. Predicting Categorical Variables 11. Predicting Changes with Time 12. Sources of Data 13. Dealing with Missing Data 14. Dealing with Messy Data 15. Dealing with Large Data 16. Working with Popular R Packages 17. Reproducibility and Best Practices 18. Other Books You May Enjoy

Using a bigger and faster machine

Instead of rewriting critical sections of your code, consider running the code on a machine with a faster processor, more cores, more RAM memory, faster bus speeds, and/or reduced disk latency. This suggestion may seem like a glib cop-out, but it's not. Sure, using a bigger machine for your analytics sometimes means extra money, but your time, dear reader, is money too. If, over the course of your work, it takes you many hours to optimize your code adequately, buying or renting a better machine may actually prove to be the more cost-effective solution.

Going down this road needn't require that you purchase a high-powered machine outrightly; there are now virtual servers that you can rent online for finite periods of time at reasonable prices. Some of these virtual servers can be configured to have 2 terabytes of RAM and 40 virtual processors...

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