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Advanced Analytics with R and Tableau

You're reading from  Advanced Analytics with R and Tableau

Product type Book
Published in Aug 2017
Publisher Packt
ISBN-13 9781786460110
Pages 178 pages
Edition 1st Edition
Languages
Authors (3):
Ruben Oliva Ramos Ruben Oliva Ramos
Profile icon Ruben Oliva Ramos
Jen Stirrup Jen Stirrup
Profile icon Jen Stirrup
Roberto Rösler Roberto Rösler
View More author details

Table of Contents (16) Chapters

Advanced Analytics with R and Tableau
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Advanced Analytics with R and Tableau 2. The Power of R 3. A Methodology for Advanced Analytics Using Tableau and R 4. Prediction with R and Tableau Using Regression 5. Classifying Data with Tableau 6. Advanced Analytics Using Clustering 7. Advanced Analytics with Unsupervised Learning 8. Interpreting Your Results for Your Audience Index

Bayesian methods


Suppose I claim that I have a pair of magic rainbow socks. I allege that whenever I wear these special socks, I gain the ability to predict the outcome of coin tosses, using fair coins, better than chance would dictate. Putting my claim to the test, you toss a coin 30 times, and I correctly predict the outcome 20 times. Using a directional hypothesis with the binomial test, the null hypothesis would be rejected at alpha-level 0.05. Would you invest in my special socks?

Why not? If it's because you require a larger burden of proof on absurd claims, I don't blame you. As a grandparent of Bayesian analysis, Pierre-Simon Laplace (who independently discovered the theorem that bears Thomas Bayes' name), once said: The weight of evidence for an extraordinary claim must be proportioned to its strangeness. Our prior belief—my absurd hypothesis—is so small that it would take much stronger evidence to convince the skeptical investor, let alone the scientific community.

Unfortunately...

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