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R for Data Science Cookbook (n)

You're reading from  R for Data Science Cookbook (n)

Product type Book
Published in Jul 2016
Publisher
ISBN-13 9781784390815
Pages 452 pages
Edition 1st Edition
Languages
Author (1):
Yu-Wei, Chiu (David Chiu) Yu-Wei, Chiu (David Chiu)
Profile icon Yu-Wei, Chiu (David Chiu)

Table of Contents (19) Chapters

R for Data Science Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. Functions in R 2. Data Extracting, Transforming, and Loading 3. Data Preprocessing and Preparation 4. Data Manipulation 5. Visualizing Data with ggplot2 6. Making Interactive Reports 7. Simulation from Probability Distributions 8. Statistical Inference in R 9. Rule and Pattern Mining with R 10. Time Series Mining with R 11. Supervised Machine Learning 12. Unsupervised Machine Learning Index

Conducting exact binomial tests


To perform parametric testing, one must assume that the data follows a specific distribution. However, in most cases, we do not know how the data is distributed. Thus, we can perform a nonparametric (that is, distribution-free) test instead. In the following recipes, we will show you how to perform nonparametric tests in R. First, we will cover how to conduct an exact binomial test in R.

Getting ready

In this recipe, we will use the binom.test function from the stat package.

How to do it…

Perform the following steps to conduct an exact binomial test:

  1. Let's assume there is a game where a gambler can win by rolling the number six on a dice. As part of the rules, the gambler can bring their own dice. If the gambler tried to cheat in the game, they would use a loaded dice to increase their chances of winning. Therefore, if we observe that the gambler won 92 games out of 315, we could determine whether the dice was likely fair by conducting an exact binomial test:

    ...
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