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]] | ||
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# [[Software_tutorial/Loading data in MATLAB or Python| Loading data in MATLAB or Python]] from Excel, CSV and XML files --> | # [[Software_tutorial/Loading data in MATLAB or Python| Loading data in MATLAB or Python]] from Excel, CSV and XML files --> | ||
* Want tutorials on other topics: please [mailto: | * Want tutorials on other topics: please [mailto:kgdunn@gmail.com 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 | <!-- * 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). | ||
--> | |||
== R-related resources == | == R-related resources == | ||
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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://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 | ||
* [http://www.twotorials.com/ The two-minute tutorials] on many R-related aspects | * [http://www.twotorials.com/ The two-minute tutorials] on many R-related aspects | ||
<!-- == Need some more help? == | <!-- | ||
* 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" | ||
Latest revision as of 12:06, 12 August 2018
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
- Another good tutorial, Quick-R: follow the links on the left-hand side
- The two-minute tutorials on many R-related aspects