Report Writing for Data Science in R
Report Writing for Data Science in R
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Report Writing for Data Science in R

Last updated on 2019-04-17

About the Book

This book teaches the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducibility is the idea that data analyses should be published or made available with their data and software code so that others may verify the findings and build upon them.  The need for reproducible report writing is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This book will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.

If you are interetsed in a printed version of this book, you can purchase one through Lulu.

About the Author

Roger D. Peng
Roger D. Peng

Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health where his research focuses on the development of statistical methods for addressing environmental health problems. He is the author of the popular book R Programming for Data Science and nine other books on data science and statistics. He is also the co-creator of the Johns Hopkins Data Science Specialization, the Simply Statistics blog where he writes about statistics for the public, the Not So Standard Deviations podcast with Hilary Parker, and The Effort Report podcast with Elizabeth Matsui. Roger is a Fellow of the American Statistical Association and is the recipient of the Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to public health. He can be found on Twitter and GitHub at @rdpeng.

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The Book
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The Book + Lecture Videos (HD)

This package includes the book and high definition lecture video files (720p). The collection also contains live demonstrations of how to use various aspects of R that could not be included in the book. The videos are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license.

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  • extras
    Lecture Videos (HD)
  • English

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Table of Contents

  • Stay in Touch!
  • 1. Getting Started with R
  • 2. What is Reproducible Reporting?
  • 3. The Data Science Pipeline
  • 4. Literate Statistical Programming
  • 5. Organizing a Data Analysis
  • 6. Structure of a Data Analysis: Part 1
  • 7. Structure of a Data Analysis: Part 2
  • 8. Markdown
  • 9. Using knitr for Reproducible Reports
  • 10. Communicating Results Over E-mail
  • 11. Reproducibility Check List
  • 12. Evidence-based Data Analysis
  • 13. Public Reproducibility Resources
  • About the Author

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