Synopses & Reviews
What exactly is data science? With this book, youll gain a clear understanding of this discipline for discovering natural laws in the structure of data. Along the way, youll learn how to use the versatile R programming language for data analysis.
Whenever you measure the same thing twice, you get two results—as long as you measure precisely enough. This phenomenon creates uncertainty and opportunity. Author Garrett Grolemund, Master Instructor at RStudio, shows you how data science can help you work with the uncertainty and capture the opportunities. Youll learn about:
- Data Wrangling—how to manipulate datasets to reveal new information
- Data Visualization—how to create graphs and other visualizations
- Exploratory Data Analysis—how to find evidence of relationships in your measurements
- Modelling—how to derive insights and predictions from your data
- Inference—how to avoid being fooled by data analyses that cannot provide foolproof results
Through the course of the book, youll also learn about the statistical worldview, a way of seeing the world that permits understanding in the face of uncertainty, and simplicity in the face of complexity.
Synopsis
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.
Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you ve learned along the way.
You ll learn how to:
- Wrangle transform your datasets into a form convenient for analysis
- Program learn powerful R tools for solving data problems with greater clarity and ease
- Explore examine your data, generate hypotheses, and quickly test them
- Model provide a low-dimensional summary that captures true "signals" in your dataset
- Communicate learn R Markdown for integrating prose, code, and results
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About the Author
Garrett Grolemund is a statistician, teacher and R developer who currently works for RStudio. He sees data analysis as a largely untapped fountain of value for both industry and science. Garrett received his Ph.D at Rice University in Hadley Wickham's lab, where his research traced the origins of data analysis as a cognitive process and identified how attentional and epistemological concerns guide every data analysis.
Garrett is passionate about helping people avoid the frustration and unnecessary learning he went through while mastering data analysis. Even before he finished his dissertation, he started teaching corporate training in R and data analysis for Revolutions Analytics. He's taught at Google, eBay, Axciom and many other companies, and is currently developing a training curriculum for RStudio that will make useful know-how even more accessible.
Outside of teaching, Garrett spends time doing clinical trials research, legal research, and financial analysis. He also develops R software, he's co-authored the lubridate R package--which provides methods to parse, manipulate, and do arithmetic with date-times--and wrote the ggsubplot package, which extends the ggplot2 package.