### 12. About the Authors
**Roger D. Peng** is an Associate Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. He is also a Co-Founder of the [Johns Hopkins Data Science Specialization](http://www.coursera.org/specialization/jhudatascience/1), which has enrolled over 1.5 million students, and the [Simply Statistics blog](http://simplystatistics.org/) where he writes about statistics and data science for the general public. Roger can be found on Twitter and GitHub [@rdpeng](https://twitter.com/rdpeng).
**Elizabeth Matsui** is a Professor of Pediatrics, Epidemiology and Environmental Health Sciences at Johns Hopkins University and a practicing pediatric allergist/immunologist. She directs a data management and analysis center with Dr. Peng that supports epidemiologic studies and clinical trials and is co-founder of [Skybrude Consulting, LLC](http://skybrudeconsulting.com), a data science consulting firm. Elizabeth can be found on Twitter [@eliza68](https://twitter.com/eliza68).
- Title Page
- 1. Data Analysis as Art
- 2. Epicycles of Analysis
- 3. Stating and Refining the Question
- 4. Exploratory Data Analysis
- 5. Using Models to Explore Your Data
- 6. Inference: A Primer
- 7. Formal Modeling
- 8. Inference vs. Prediction: Implications for Modeling Strategy
- 9. Interpreting Your Results
- 10. Communication
- 11. Concluding Thoughts
- 12. About the Authors