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Learning Predictive Analytics with R

You're reading from  Learning Predictive Analytics with R

Product type Book
Published in Sep 2015
Publisher Packt
ISBN-13 9781782169352
Pages 332 pages
Edition 1st Edition
Languages
Author (1):
Eric Mayor Eric Mayor
Profile icon Eric Mayor

Table of Contents (23) Chapters

Learning Predictive Analytics with R
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Setting GNU R for Predictive Analytics Visualizing and Manipulating Data Using R Data Visualization with Lattice Cluster Analysis Agglomerative Clustering Using hclust() Dimensionality Reduction with Principal Component Analysis Exploring Association Rules with Apriori Probability Distributions, Covariance, and Correlation Linear Regression Classification with k-Nearest Neighbors and Naïve Bayes Classification Trees Multilevel Analyses Text Analytics with R Cross-validation and Bootstrapping Using Caret and Exporting Predictive Models Using PMML Exercises and Solutions Further Reading and References Index

Probability distributions


In this section, we very briefly examine important distributions for common statistical problems with data consisting of quantities: the normal distribution and Student's t-distributions. We first introduce the idea of distributions with a discrete uniform distribution. We conclude with binomial distribution. We will try to be as non-technical as possible in this introduction to allow readers without statistical knowledge to follow easily; however, don't worry, we will be highly technical when explaining how to build functions that estimate correlations and regression coefficients.

Introducing probability distributions

Here, we introduce the idea of distributions using discrete uniform and binomial distributions.

Discrete uniform distribution

You might remember that, in Chapter 2, Visualizing and manipulating data using R, we examined outcomes of the roulette game. We showed that each of the 37 numbers (0 to 36) in European roulette has an equal probability of occurring...

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