Difference between revisions of "Software tutorial"
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* Tutorial on removing white space around figures | |||
* Add tutorial on drawing lines (cf the "line" vs "lines" function) | |||
* Add tutorial on font sizes for plots, axis labels, and category labels (bar plot). See univariate/code/histogram-children-by-gender.R | |||
* Adding formula to labels: main=(expression(""*mu*"=0")) | |||
* Add tutorial from: https://servera/knol/index.php/R_tips | |||
yahoo2 <- yahoo[ yahoo$date >= as.Date('2008-01-01'), ] | |||
plot(x=yahoo2$date, y=yahoo2$close, main='YHOO stock close', xlab='date', ylab='close ($)') | |||
plot.ts function | |||
== Need some more help? == | |||
{| class="wikitable" | {| class="wikitable" |
Revision as of 18:45, 9 March 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
- 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
- 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).
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