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Data Analysis with R

You're reading from  Data Analysis with R

Product type Book
Published in Dec 2015
Publisher
ISBN-13 9781785288142
Pages 388 pages
Edition 1st Edition
Languages
Toc

Table of Contents (20) Chapters close

Data Analysis with R
Credits
About the Author
About the Reviewer
www.PacktPub.com
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. Predicting Continuous Variables 9. Predicting Categorical Variables 10. Sources of Data 11. Dealing with Messy Data 12. Dealing with Large Data 13. Reproducibility and Best Practices Index

Communicating results


Unless an analysis is performed solely for the personal edification of the analyst, the results are going to be communicated—either to teammates, your company, your lab, or the general public. Some very advanced technologies are in place for R programmers to communicate their results accurately and attractively.

Following the pattern of some of the other sections in this chapter, we will talk about a range of approaches starting with a bad alternative and give an explanation for why it's inadequate.

The terrible solution to the creating of a statistical report is to copy R output into a Word document (or PowerPoint presentation) mixed with prose. Why is this terrible? you ask? Because if one little thing about your analysis changes, you will have to re-copy the new R output into the document, manually. If you do this enough times, it's not a matter of if but a matter of when you will mess up and copy the wrong thing, or forget to copy the new output, and so on. This method...

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