Difference between revisions of "Software tutorial"
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# Linear models with multiple X-variables (MLR) | # Linear models with multiple X-variables (MLR) | ||
# Linear models with integer variables --> | # Linear models with integer variables --> | ||
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# [[Software tutorial/Loops|<tt>for</tt> loops and <tt>while</tt> loops]] (required for [[Tutorial_1_-_2010|tutorial 1]]) | # [[Software tutorial/Loops|<tt>for</tt> loops and <tt>while</tt> loops]] (required for [[Tutorial_1_-_2010|tutorial 1]]) | ||
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== R-related resources == | |||
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. | ||
* [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 | |||
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Revision as of 22:08, 15 January 2013
This tutorial will expand as we progress in the course.
- 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
- 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 is currently running.
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