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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

  • Write a function called dt_table similar to the table function in base R. The arguments will be a data.table, and a string specifying a column name. Do the same thing for tibbles and call it dp_table.
  • Read some of the documentation for data.table and dplyr/tidyr . Of the former, learn about .SD and .SDcols. Of the later, learn about the separate_ functions. These are life-savers.
  • Learn about some of the other popular packages of the tidyverse. What do all of these have in common, again?
  • Describe the four major voting bloc "cleavages" defined by Lipset and Rokkan in Party systems and voter alignments. Since its publication in 1967, have any other potential cleavage points emerged in your nation or state? How do these cleavages manifest themselves in political party differences?
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