Book Image

Data Analysis with R, Second Edition - Second Edition

Book Image

Data Analysis with R, Second Edition - Second Edition

Overview of this book

Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst.
Table of Contents (24 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

What's... uhhh... the deal with the bootstrap?


You may be pleased to hear that you, dear reader, are already set up for a keen understanding of the bootstrap based on the material in Chapter 5, Using Data to Reason about the World. Specifically, recall how the subject of sampling distributions of sample means was broached (if you need to refer back to the section, please do!). In our very hands-on creation of our first sampling distribution of sample means, we created a vector of 10,000 normally distributed (mean of 65, and standard deviation of 3.5) values representing a population of the heights of US women in inches. We then took 10,000 samples of size 40 from this population, took means of those samples, and plotted this distribution.

Call to mind that this sampling distribution had a mean equal to the population mean, and a standard deviation of population standard deviation divided by the square root of the sample size. Recall that the standard deviation of the sampling distribution...