Difference between revisions of "Software tutorial"
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The tutorial below is intended to be a self-directed learning experience for the R statistical language. (Another highly-recommended tutorial is [https://www.datacamp.com/courses/free-introduction-to-r available here]) | |||
# [[Software tutorial/About the course software | About the course software]] | # [[Software tutorial/About the course software | About the course software]] | ||
Revision as of 13:31, 2 January 2016
The tutorial below is intended to be a self-directed learning experience for the R statistical language. (Another highly-recommended tutorial is available here)
- 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