Difference between revisions of "Software tutorial"
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Not every aspect about R can be covered with our tutorial (above). Here are some additional resources. | Not every aspect about R can be covered with our tutorial (above). Here are some additional resources. | ||
* [ | * [https://en.wikipedia.org/wiki/R_(programming_language) Wikipedia page about R] | ||
* [http://wiki.stdout.org/rcookbook/ Cookbook for R]: how to work with numbers, manipulate data, statistical analysis, graphs, debug scripts | * [http://wiki.stdout.org/rcookbook/ Cookbook for R]: how to work with numbers, manipulate data, statistical analysis, graphs, debug scripts | ||
* [http://www.statmethods.net/index.html Another good tutorial, Quick-R]: follow the links on the left-hand side | * [http://www.statmethods.net/index.html Another good tutorial, Quick-R]: follow the links on the left-hand side | ||
Revision as of 13:09, 2 January 2016
This tutorial is intended to be a self-directed learning experience for the R statistical language.
- About the course software
- Software installation
- Getting started
- Reading data into R
- Basic data manipulation in R
- Basic plots in R
- Plots with multiple series, colour, and legends
- Histograms
- Annotating plots: grid lines, arrows, lines, and identifying interesting points
- Dealing with factors (categorical variables)
- Calculating statistics from a data sample
- Dealing with distributions
- Extending R with packages
- Programming in R: loops and flow control
- Vectors and matrices
- Building a least squares model in R
- Extracting information from a linear model in R
- Testing a linear model in R
- Transformation of data in a linear model
- Investigating outliers, discrepancies and other influential points
- Linear models with multiple X-variables (MLR)
- Linear models with integer variables
- Want tutorials on other topics: please email me
Not every aspect about R can be covered with our tutorial (above). Here are some additional resources.
- Wikipedia page about R
- 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