Difference between revisions of "Software tutorial"
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* Want tutorials on other topics: please [mailto:kevin.dunn@mcmaster.ca email me] | * Want tutorials on other topics: please [mailto:kevin.dunn@mcmaster.ca email me] | ||
* A note about the videos in this tutorial: they are from [http://www.youtube.com/playlist?list=PLjTlxb-wKvXPqyY3FZDO8GqIaWuEDy-Od Roger Peng's YouTube] channel on R Videos. He is running a MOOC on [https://class.coursera.org/compdata-002 Computing for Data Analysis] which started on 2 January, and has recently finished (February 2012). | <!-- * A note about the videos in this tutorial: they are from [http://www.youtube.com/playlist?list=PLjTlxb-wKvXPqyY3FZDO8GqIaWuEDy-Od Roger Peng's YouTube] channel on R Videos. He is running a MOOC on [https://class.coursera.org/compdata-002 Computing for Data Analysis] which started on 2 January, and has recently finished (February 2012). | ||
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== R-related resources == | == R-related resources == | ||
Revision as of 19:37, 14 July 2014
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.
- 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.
- 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