• R is a language and environment for statistical computing and graphics
• Open source
• The most widely used statistical software in the world
• Amazing number of contributors

Who use R?

• Researchers
• Data analysts
• Programmers
• Journalists
• Web designers

• In academia R de-facto is the standard tool

Illustration

https://www.r-users.com

https://www.demogr.mpg.de/en/education_career/jobs_fellowships_1910/statistical_analyst_4828.htm

http://blog.revolutionanalytics.com/2014/05/companies-using-r-in-2014.html

Why R?

“R offers a breadth and depth in statistical computing beyond what is available in commercial closed source products. Yet R remains, primarily, a programming language for the highly skilled statistician, and out of the reach of many.”

Williams, G. J. (2009). Rattle: A Data Mining GUI for R. The R Journal, 1/2, 45-55.

PRO

• Open source
• Reproducible
• Easy and fast to work with large datasets

• Most importantly, R can easily replace most of the tools one uses daily for research

CONTRA

• Steep learning curve
• Not perfect for handling survey data (metadata)

https://ourworldindata.org

https://jschoeley.shinyapps.io/hmdexp

Election 2016: Exit Polls

http://www.nytimes.com/interactive/2016/11/08/us/politics/election-exit-polls.html

A Day in the Life of Americans

http://flowingdata.com/2015/12/15/a-day-in-the-life-of-americans

Where People Run in Major Cities

http://flowingdata.com/2014/02/05/where-people-run/

https://youtu.be/aOtQyfbRMQY

Reproducibility

• Reproducibility of scientific results is the main challenge of the modern academia
• Collaboration, Open Science (2015). Estimating the reproducibility of psychological science. Science, 349(6251), aac4716. https://doi.org/10.1126/science.aac4716
• Out of 100 papers only 39 were replicated

Literate programming

• The idea of literate programming dates back to mid-80s
• The core idea: code, comments, and results should appear together in one document.

R notebooks

• The recently presented v1.0 version of RStudio brings R-notebooks as on of the main features.
  
• This type of document implements the principles of literate programming.

http://www.danielwells.me/human-lifespan-limit/

Swirl

• install.packages('swirl')
• library(swirl)
• swirl()

The most influential R developer

Hadley Wickham

tidyverse

https://blog.rstudio.org/2016/09/15/tidyverse-1-0-0/

tidy data

Wickham, H. (2014). Tidy Data. Journal of Statistical Software, 59(10). Retrieved from http://www.jstatsoft.org/v59/i10

Tidy data is a standard way of mapping the meaning of a dataset to its structure.

A dataset is messy or tidy depending on how rows, columns and tables are matched up with observations, variables and types.

In tidy data:

1. Each variable forms a column.
2. Each observation forms a row.
3. Each type of observational unit forms a table.

• Please follow me on the R script "examples-tidyverse.R"
• Then proceed to "exercises.R"