This is a small document. It exists mainly to demonstrate some features of RMarkdown.
This section is an excuse to make a bibliography. The first step is in the last line in the YAML header above. Also notice the tags beginning with @ in the next few paragraphs.
Have you read any good books lately? I recently came across Annihilation (Vandermeer 2014) which I liked so much I read another book called Borne by the same author (2017). The film version of Annihilation was not so good in my opinion. More recently I read Drive Your Plough Over the Bones of the Dead (Tokarczuk 2019). It was amazing. I saw a film version but it had a different name. Another book I liked is The Overstory by Richard Powers (Powers 2018). It’s a long book and it required two attempts to finish. The first time I gave up because it was a lot to keep track of. A year later I tried again and I liked it more. It still took a long time to read.
It’s not difficult to find statistics textbooks which begin with a section on descriptive statistics. For example consider the book we used for MATH 3302 (Vandermeer 2014). It is, however, difficult to find a good definition of data science. I like the approach taken in this paper by David Donoho. (Donoho 2017)
A .bib file is plain text. You can open it in any simple editor. The Wikipedia page lists the types of entries and the fields that are available for each. There are other websites with similar info, like this one. You can also use a bibtex IDE to make things faster. This file used BibDesk for MacOS. Other tools are available for Windows and Linux.
By now you’ve figured out that TOC means Table of Contents.
Adding a table of contents means setting parameters in the YAML
header. These are toc, toc_depth, and
number_sections. Notice how setting these is different from
setting the bibliography parameter.
Scroll up to see the section structure of this document.
Examples below show how to make a hierarchy of sections. Be careful.
Be careful. Don’t go nuts with this.
Leonhard Euler was arguably one of the greatest mathematicians of the 18th century. Euler’s exceptional mathematical expertise is evident in his significant productivity, which outshines that of any other mathematician in history. His work spanned various branches of mathematics, physics, and astronomy, leaving an indelible mark on these disciplines. Despite losing his sight at the age of sixty four, Euler’s mathematical productivity continued, making him a true mathematical giant. Born in Switzerland, he overcame challenges in pursuit of recognition, ultimately finding prominence in Russia and Germany. Euler’s extensive publication list, comprising of nearly 900 papers and books, solidifies his status as one of history’s most productive mathematicians (Lim 2024). His legacy includes foundational contributions to calculus, number theory, topology, and more, often accompanied by the introduction of modern mathematical notation and terminology. Euler’s influence extended beyond his era, earning him recognition as one of the greatest mathematicians of all time. In the words of Pierre-Simon Laplace, “Read Euler, read Euler, he is a master for us all,” (Dunham 1999) attesting to the enduring impact of Euler’s work on the field of mathematics. [“Leonhard Euler” (2025)](R Core Team 2021)