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Data Analysis with R, Second Edition - Second Edition

You're reading from Data Analysis with R, Second Edition - Second Edition

Product type Book

Published in Mar 2018

Publisher Packt

ISBN-13 9781788393720

Pages 570 pages

Edition 2nd Edition

Languages

Concepts

Table of Contents (24) Chapters

Title Page

Copyright and Credits

Packt Upsell

Contributors

Preface

1. RefresheR

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

1. Other Books You May Enjoy

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Index

Exercises

Learn more about the other measures of accuracy provided by forecast function's accuracy function. What advantages does MAPE have over RMSE/MAE
Learn how to interpret the alpha, beta, gamma, (and sometimes phi) parameters of an ETS object. What does it mean to have a low beta parameter? Try to explicitly specify extreme values for some of these parameters using named arguments in the ets function. How does it affect the quality and dynamics of your forecasts?
The GitHub repository that we used to download some of the data sets in this chapter (and we will be using for different data sets for subsequent chapters, as well) also contains a data set containing Google searches for Dr. Martin Luther King, Jr., what example series in this chapter does this most resemble? Is there seasonality in this series? If so, when do the spikes in searches occur? Why do you think that is? Take your best guess as to which particular ETS model ets would chose to describe this series. Try it for yourself...

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