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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

Exercises

  • Find a freely available government dataset on the web. Read the dataset's description, and think about what assumptions you might make about the data when planning a certain analysis. Translate these into actual code so that R can check them for you. Were there any deviations from your expectations?
  • An ISBN-10 is a unique identifier for books. It is 10 characters long. The last digit is called a check digit and is determinable from the preceding digits using modular arithmetic. When the check digit is "10", it is represented with an "X". To review, an ISBN-10 is either 10 digits or nine digits, with an "X" at the end. Write a function that uses regular expressions to check if an input string (or vector of strings) is in the forma
t of a valid ISBN-10. As a bonus, write code to check if the check digit matches what it is supposed...
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