Chapter 1 Introduction

1.1 Getting started

These tutorials will be done in R using RStudio as a front end. You will need to either download R and RStudio (both are free) onto your own computer or use them on Pomona’s server.

  • You may use R on the Pomona server: https://rstudio.pomona.edu/ (All Pomona students will be able to log in immediately. Non-Pomona students need to go to ITS at Pomona to get Pomona login credentials.)
  • If you want to use R on your own machine, you may. Please make sure all components are updated: R is freely available at http://www.r-project.org/ and is already installed on college computers. Additionally, installing R Studio is required http://rstudio.org/.
  • http://swirlstats.com/ is one way to walk through learning the basics of R.
  • All assignments should be turned in using R Markdown compiled to pdf.

1.2 Reproducibility

1.2.1 The reproducible data analysis process

  • Scriptability \(\rightarrow\) R
  • Literate programming \(\rightarrow\) R Markdown
  • Version control \(\rightarrow\) Git / GitHub

Scripting and literate programming

Donald Knuth “Literate Programming” (1983)

Let us change our traditional attitude to the construction of programs: Instead of imagining that our main task is to instruct a computer- what to do, let us concentrate rather on explaining to human beings- what we want a computer to do.

  • The ideas of literate programming have been around for many years!
  • and tools for putting them to practice have also been around
  • but they have never been as accessible as the current tools

Reproducibility checklist

  • Are the tables and figures reproducible from the code and data?
  • Does the code actually do what you think it does?
  • In addition to what was done, is it clear why it was done? (e.g., how were parameter settings chosen?)
  • Can the code be used for other data?
  • Can you extend the code to do other things?

Tools: R & R Studio

See this great video (less than 2 min) on a reproducible workflow: https://www.youtube.com/watch?v=s3JldKoA0zw&feature=youtu.be

  • You must use both R and RStudio software programs
  • R does the programming
  • R Studio brings everything together
  • You may use Pomona’s server: https://rstudio.pomona.edu/
Taken from [Modern Drive: An introduction to statistical and data sciences via R](https://ismayc.github.io/moderndiver-book/), by Ismay and Kim

Figure 1.1: Taken from Modern Drive: An introduction to statistical and data sciences via R, by Ismay and Kim

[Jessica Ward](https://jkrward.github.io/), PhD student at Newcastle University

Figure 1.2: Jessica Ward, PhD student at Newcastle University

1.3 reprex

Help me help you

In order to create a reproducible example …

Step 1. Copy code onto the clipboard

Step 2. Type reprex() into the Console

Step 3. Look at the Viewer to the right. Copy the Viewer output into GitHub, Piazza, an email, stackexchange, etc.

Some places to learn more about reprex include

1.3.0.1 reprex demo

reprex(
  jan31 + months(0:11) + days(31)
)

multiple lines of code:

reprex({
  jan31 <- ymd("2013-01-31")
  jan31 + months(0:11) + days(31)
})
reprex({
  library(lubridate)
  jan31 <- ymd("2013-01-31")
  jan31 + months(0:11) + days(31)
})