The Elements of Data Analytic Style
A guide for people who want to analyze data.
By Jeff Leek
About the Book
Data analysis is at least as much art as it is science. This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. It is based in part on the authors blog posts, lecture materials, and tutorials such as:
10 things statistics taught us about big data analysis
The Leek Group Guide to R packages
How to share data with a statistician
The author is one of the co-developers of the Johns Hopkins Specialization in Data Science the largest data science program in the world that has enrolled more than 1.76 million people. The book is useful as a companion to introductory courses in data science or data analysis. It is also a useful reference tool for people tasked with reading and critiquing data analyses.
Table of Contents
1. Introduction
2. The data analytic question
3. Tidying the data
4. Checking the data
5. Exploratory analysis
6. Statistical modeling and inference
7. Prediction and machine learning
8. Causality
9. Written analyses
10. Creating figures
11. Presenting data
12. Reproducibility
13. A few matters of form
14. The data analysis checklist
15. Additional resources
Jeff Leek is an Associate Professor of Biostatistics and Oncology at the Johns Hopkins Bloomberg School of Public Health. His research focuses on the intersection of high dimensional data analysis, genomics, and public health. He is the co-editor of the popular Simply Statistics Blog and co-director of the Johns Hopkins Specialization in Data Science the largest data science program in the world that has enrolled more than 1.76 million people.