Welcome
Welcome to the bs4 output from the oxforddown thesis template for R Markdown.
To view/download the PDF output, click here (or click the cover image).
Enjoy!
Abstract
This R Markdown template is for writing an Oxford University thesis. The template is built using Yihui Xie’s bookdown package, with heavy inspiration from Chester Ismay’s thesisdown and the OxThesis template (most recently adapted by John McManigle).
This template’s sample content include illustrations of how to write a thesis in R Markdown, and largely follows the structure from this R Markdown workshop.
Congratulations for taking a step further into the lands of open, reproducible science by writing your thesis using a tool that allows you to transparently include tables and dynamically generated plots directly from the underlying data. Hip hooray!
Acknowledgments
This is where you will normally thank your advisor, colleagues, family and friends, as well as funding and institutional support. In our case, we will give our praises to the people who developed the ideas and tools that allow us to push open science a little step forward by writing plain-text, transparent, and reproducible theses in R Markdown.
We must be grateful to John Gruber for inventing the original version of Markdown, to John MacFarlane for creating Pandoc (http://pandoc.org) which converts Markdown to a large number of output formats, and to Yihui Xie for creating knitr which introduced R Markdown as a way of embedding code in Markdown documents, and bookdown which added tools for technical and longer-form writing.
Special thanks to Chester Ismay, who created the thesisdown package that helped many a PhD student write their theses in R Markdown. And a very special thanks to John McManigle, whose adaption of Sam Evans’ adaptation of Keith Gillow’s original maths template for writing an Oxford University DPhil thesis in LaTeX provided the template that I in turn adapted for R Markdown.
Finally, profuse thanks to JJ Allaire, the founder and CEO of RStudio, and Hadley Wickham, the mastermind of the tidyverse without whom we’d all just given up and done data science in Python instead. Thanks for making data science easier, more accessible, and more fun for us all.