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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

Choosing a prior


Notice that the posterior distribution looks a little different depending on what prior you use. The most common criticism lodged against Bayesian methods is that the choice of prior adds an unsavory subjective element to analysis. To a certain extent, they're right about the added subjective element, but their allegation that it is unsavory is way off the mark.

To see why, check out Figure 7.6, which shows both posterior distributions (from priors #1 and #2) in the same plot. Notice how priors #1 and #2—two very different priors—given the evidence, produce posteriors that look more similar to each other than the priors did.

Figure 7.6: The posterior distributions from prior #1 and #2

Now direct your attention to Figure 7.7, which shows the posterior of both priors if the evidence included 80 out of 120 correct trials.

Figure 7.7: The posterior distributions from prior #1 and #2 with more evidence

Note that the evidence still contains 67% correct trials, but there is now more...

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