Topics

• Reproducible data analysis
• R and RStudio
• R Markdown
• Git and GitHub

Reproducibility checklist

Near-term goals

✔️ 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?

Long-term goals

✔️ Can the code be used for other data?

✔️ Can you extend the code to do other things?

Toolkit

• Scriptability → R

• Literate programming (code, narrative, output in one place) → R Markdown

• Version control → Git / GitHub

What is R and RStudio?

• R is a statistical programming language

• RStudio is a convenient interface for R (an integrated development environment, IDE)

R essentials (a short list)

• Functions are (most often) verbs, followed by what they will be applied to in parentheses:

do_this(to_this)
do_that(to_this, to_that, with_those)

• Columns (variables) in data frames are accessed with $:

dataframe$var_name

• Packages are installed with the install.packages function and loaded with the library function, once per session:

install.packages("package_name")
library(package_name)

tidyverse

R Markdown

• Fully reproducible reports -- the analysis is run from the beginning each time you knit

• Simple Markdown syntax for text

• Code goes in chunks, defined by three backticks, narrative goes outside of chunks

How will we use R Markdown?

• Every assignment / lab / project / etc. is an R Markdown document

• You'll always have a template R Markdown document to start with

• The amount of scaffolding in the template will decrease over the semester

R Markdown tips

Resources

• R Markdown cheat sheet
• Markdown Quick Reference:
  • Help -> Markdown Quick Reference
    
    

Remember: The workspace of the R Markdown document is separate from the console

Version control

• We introduced GitHub as a platform for collaboration

• But it's much more than that...

• It's actually designed for version control

What is versioning?

What is versioning?

with human readable messages

Why do we need version control?

• Git is a version control system -- like “Track Changes” features from Microsoft Word.

• GitHub is the home for your Git-based projects on the internet (like DropBox but much better).

• There are a lot of Git commands and very few people know them all. 99% of the time you will use git to add, commit, push, and pull.

Git and GitHub tips

• We will be doing git things and interfacing with GitHub through RStudio
  • If you Google for help, skip any methods for using git through the command line.

• There is a great resource for working with git and R: happygitwithr.com.
  • Some of the content in there is beyond the scope of this course, but it's a good place to look for help.

Recap

Can you answer these questions?

• What is a reproducible data analysis, and why is it important?
• What is version control, and why is it important?
• What is R vs. RStudio?
• What is git vs. GitHub?