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Reproducible research with R and R Studio / Christopher Gandrud.

By: Series: Chapman & Hall/CRC the R series (CRC Press)Publisher: Boca Raton : CRC Press/Taylor & Francis Group, [2014]Description: xxv, 288 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781466572843
  • 1466572841
Subject(s): DDC classification:
  • 001.4/2202855133 23
LOC classification:
  • Q180.55.S7 G36 2014
Other classification:
  • MAT029000
  • 70.03
  • ST 250
  • NN3
Contents:
Introducing reproducible research -- Getting started with reproducible research -- Getting started with R, RStudio, and knitr -- Getting started with file management -- Data gathering and storage storing, collaborating, accessing files, and versioning -- Gathering data with R -- Preparing data for analysis -- Analysis and results statistical modeling and knitr -- Showing results with tables -- Showing results with figures -- Presentation documents Presenting with LaTeX -- Large LaTeX documents: theses, books, and batch reports -- Presenting on the web with markdown -- Conclusion.
Summary: "Preface This book has its genesis in my PhD research at the London School of Economics. I started the degree with questions about the 2008/09 financial crisis and planned to spend most of my time researching about capital adequacy requirements. But I quickly realized much of my time would actually be spent learning the day-to-day tasks of data gathering, analysis, and results presentation. After plodding through for awhile, the breaking point came while reentering results into a regression table after I had tweaked one of my statistical models, yet again. Surely there was a better way to do research that would allow me to spend more time answering my research questions. Making research reproducible for others also means making it better organized and efficient for yourself. So, my search for a better way led me straight to the tools for reproducible computational research. The reproducible research community is very active, knowledgeable and helpful. Nonetheless, I often encountered holes in this collective knowledge, or at least had no resource to bring it all together as a whole. That is my intention for this book: to bring together the skills I have picked up for actually doing and presenting computational research. Hopefully, the book along with making reproducible research more common, will save researchers hours of Googling, so they can spend more time addressing their research questions. I would not have been able to write this book without many people's advice and support. Foremost is John Kimmel, acquisitions editor at Chapman & Hall. He approached me with in Spring 2012 with the general idea and opportunity for this book"-- Provided by publisher.
Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
BOOK BOOK NCAR Library Mesa Lab Q180.55 .S7 .G36 2014 1 Available 50583020011684
Total holds: 0

Includes bibliographical references (pages 271-277) and index.

Introducing reproducible research -- Getting started with reproducible research -- Getting started with R, RStudio, and knitr -- Getting started with file management -- Data gathering and storage storing, collaborating, accessing files, and versioning -- Gathering data with R -- Preparing data for analysis -- Analysis and results statistical modeling and knitr -- Showing results with tables -- Showing results with figures -- Presentation documents Presenting with LaTeX -- Large LaTeX documents: theses, books, and batch reports -- Presenting on the web with markdown -- Conclusion.

"Preface This book has its genesis in my PhD research at the London School of Economics. I started the degree with questions about the 2008/09 financial crisis and planned to spend most of my time researching about capital adequacy requirements. But I quickly realized much of my time would actually be spent learning the day-to-day tasks of data gathering, analysis, and results presentation. After plodding through for awhile, the breaking point came while reentering results into a regression table after I had tweaked one of my statistical models, yet again. Surely there was a better way to do research that would allow me to spend more time answering my research questions. Making research reproducible for others also means making it better organized and efficient for yourself. So, my search for a better way led me straight to the tools for reproducible computational research. The reproducible research community is very active, knowledgeable and helpful. Nonetheless, I often encountered holes in this collective knowledge, or at least had no resource to bring it all together as a whole. That is my intention for this book: to bring together the skills I have picked up for actually doing and presenting computational research. Hopefully, the book along with making reproducible research more common, will save researchers hours of Googling, so they can spend more time addressing their research questions. I would not have been able to write this book without many people's advice and support. Foremost is John Kimmel, acquisitions editor at Chapman & Hall. He approached me with in Spring 2012 with the general idea and opportunity for this book"-- Provided by publisher.

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