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

Summary


One of the hardest things about data analysis is statistics, and one of the hardest things about statistics (not unlike computer programming) is that the beginning is the toughest hurdle because the concepts are so new and unfamiliar. As a result, some might find this to be one of the more challenging chapters in this text.

However, hard work during this phase pays enormous dividends; it provides a sturdy foundation on which to pile on and organize new knowledge.

To recap, in this chapter, you learned about univariate data. You also learned about:

  • The types of univariate data
  • How to measure the central tendency of this data
  • How to measure the spread of this data
  • How to visualize the shape of this data

Along the way, we also discussed a little bit about probability distributions and population/sample statistics.

I'm glad you made it through! Relax, make yourself a mocktail, and I'll see you in Chapter 3, Describing Relationships shortly!