Software tutorial

This tutorial is intended to be a self-directed learning experience for the R statistical language. We will provide a similar tutorial for Python in 2014/2015.

1. About the course software
2. Software installation
3. Getting started
4. Reading data into R
5. Basic data manipulation in R
6. Basic plots in R
7. Plots with multiple series, colour, and legends
8. Histograms
9. Annotating plots: grid lines, arrows, lines, and identifying interesting points
10. Dealing with factors (categorical variables)
11. Calculating statistics from a data sample
12. Dealing with distributions
13. Extending R with packages
14. Programming in R: loops and flow control
15. Vectors and matrices
16. Building a least squares model in R
17. Extracting information from a linear model in R
18. Testing a linear model in R
19. Transformation of data in a linear model
20. Investigating outliers, discrepancies and other influential points
21. Linear models with multiple X-variables (MLR)
22. Linear models with integer variables

• Want tutorials on other topics: please email me
• A note about the videos in this tutorial: they are from Roger Peng's YouTube channel on R Videos. He is running a MOOC on Computing for Data Analysis which started on 2 January, and has recently finished (February 2012).

R-related resources

Not every aspect about R can be covered with our tutorial (above). Here are some additional resources.

• Cookbook for R: how to work with numbers, manipulate data, statistical analysis, graphs, debug scripts
• Another good tutorial, Quick-R: follow the links on the left-hand side
• The two-minute tutorials on many R-related aspects