This page will feature slides from our sessions, exercises for you to complete, and their solutions (all to follow). Prior to the module, please install up-to-date versions of R and RStudio on the laptop you will use during the summer institute. Both are free.

• R is available from this list of sites.
• RStudio is available here.

Script files are posted following each session; these will contain our R code for the exercises. To make them work on your computer, remember to modify file names and locations appropriately. Also note that many different 'correct' solutions are possible.

Session 1, Introductions, reading in data. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 2, More data summary and using functions. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 3, Plotting functions, and formulas. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 4, Adding features to plots. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 5, Over and over. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 6, More loops, Control Structures, and Bootstrapping. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 7, Fitting models. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 8, Introduction to R packages. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Game of Life for the Special Exercise [.docx, .pdf]. This is a more in-depth programming problem, for you to try in the evening. This session's slides should help with the Exercise, we'll discuss some other approaches in the final session. To help/inspire you, here are;

• The code from the slides, as a .R file
• An animated GIF showing the Game of Life
• Some examples of growth and gliding -- produced in R
• A Gospel Glider Gun, as a text file - so you can use read.table() to bring it into R.

Session 9, Writing functions. Code from the slides [.R] Exercises [.docx, .pdf] (R script file)

Session 10 [updated], The End! No exercises for this session

• Script file for the Special Exercise
• An animated GIF showing the Game of Life
• An introductory Markdown file:
  • Source code [.Rmd]
  • PDF output [.pdf]
  • Word output [.docx]
  • HTML output [.html]
• Tim's Introduction to ggplot2 presentation
• ... and the R Markdown file that made it
• Script files ui.R, server.R and data file for the shiny/salary example. This app is available online
• Shiny's gallery shows much more functionality than we have time to mention
  
  
• Comments forms and attendance certificates are available here - requires SISG account

For easier searching, here are all the slides in one document (PDF).

Before trying to read data into your R session, we recommend looking at it first, in a text editor. Is the data comma- or tab-delimited? Does it have a 'header' row containing variable names?

• crab.csv, crab.txt
• lawschool.csv, lawschool.txt
• mammals.csv, mammals.txt
• othercrab.csv
• salary.csv, salary.txt
• titanic.csv, titanic.txt
• titaniclong.csv, titaniclong.txt

• The R site, which includes the Comprehensive R Archive Network (CRAN) of downloads and packages
• A reference card of common R commands (and a slightly longer reference card)
• A cheat sheet for ggplot
• The R Graphics Gallery has a good selection of examples - most are more complicated than those seen in our slides
• Some R mailing lists - joining the announce list is recommended. CrossValidated is also helpful (but search it before posting)
• The Elements of R course - the next level of programming, oriented for genetics/bioinformatics
• An Advanced R course - also for genetics/bioinformatics
• To change languages, put a .Renviron file in the startup working directory - use en for English, or de, it (To get the working directory, use getwd())

• P. Dalgaard, Introductory Statistics with R: Springer, 2nd Edition 2008 [good if you haven't seen much statistics before, though it uses very simple methods, and doesn't emphasize programming much. There are several other texts at this level]
• Matloff, The Art of R Programming, 2011; goes from introductory programming up to a high level.
• Braun and Murdoch, A First Course in Statistical Programming with R, CUP 2007 [A different emphasis from the other books here, good for those new to programming]