Difference between revisions of "Software tutorial"

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This tutorial will expand as we progress in the course. Each section has notes for both MATLAB and Python.
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]]
# [[Software tutorial/Software installation | Software installation]]
# [[Software tutorial/Software installation | Software installation]]
# [[Software tutorial/Getting started|Getting started]]
# [[Software tutorial/Getting started|Getting started]]
<!-- # [[Software tutorial/My first program|My first program]] (required for [[Tutorial_1_-_2010|tutorial 1]])
# [[Software tutorial/Reading data into R|Reading data into R]]
# [[Software tutorial/Basic data manipulation in R|Basic data manipulation in R]]
# [[Software tutorial/Basic plots in R|Basic plots in R]]
# [[Software tutorial/Plots with multiple series, colour, and legends|Plots with multiple series, colour, and legends]]
# [[Software tutorial/Histograms|Histograms]]
# [[Software tutorial/Annotating plots: grid lines, arrows, lines, and identifying interesting points|Annotating plots: grid lines, arrows, lines, and identifying interesting points]]
# [[Software tutorial/Dealing with factors (categorical variables)|Dealing with factors (categorical variables)]]
# [[Software tutorial/Calculating statistics from a data sample|Calculating statistics from a data sample]]
# [[Software tutorial/Dealing with distributions|Dealing with distributions]]
# [[Software tutorial/Extending R with packages|Extending R with packages]]
# [[Software tutorial/Programming in R: loops and flow control|Programming in R: loops and flow control]]
# [[Software tutorial/Vectors and matrices|Vectors and matrices]]
# [[Software tutorial/Building a least squares model in R|Building a least squares model in R]]
# [[Software tutorial/Extracting information from a linear model in R|Extracting information from a linear model in R]]
# [[Software tutorial/Testing a linear model in R|Testing a linear model in R]]
# [[Software tutorial/Transformation of data in a linear model|Transformation of data in a linear model]]
# [[Software tutorial/Investigating outliers, discrepancies and other influential points|Investigating outliers, discrepancies and other influential points]]
# [[Software tutorial/Linear models with multiple X-variables (MLR)|Linear models with multiple X-variables (MLR)]]
# [[Software tutorial/Linear models with integer variables|Linear models with integer variables]]
 
<!--
# [[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]])
# [[Software tutorial/Scripts and functions|Scripts and functions]] (useful for [[Tutorial_2_-_2010|tutorial 2]])
# [[Software tutorial/Scripts and functions|Scripts and functions]] (useful for [[Tutorial_2_-_2010|tutorial 2]])
# [[Software tutorial/Vectors and arrays|Vectors and arrays]] (used for [[Tutorial_3_-_2010|tutorial 3]])
# [[Software_tutorial/Matrix_operations|Matrix operations]] (used for [[Tutorial_4_-_2010|tutorial 4]])
# [[Software_tutorial/Functions as objects|Functions as objects]] (used for [[Tutorial_5_-_2010|tutorial 5]] to find the zero of a function)
# [[Software_tutorial/Functions as objects|Functions as objects]] (used for [[Tutorial_5_-_2010|tutorial 5]] to find the zero of a function)
# [[Software_tutorial/Creating and saving plots|Creating and saving plots]] : important for all remaining assignments, and the take-home exam.
# [[Software_tutorial/Creating and saving plots|Creating and saving plots]] : important for all remaining assignments, and the take-home exam.
# [[Software_tutorial/Integration of ODEs|Integrating ODEs]]: a tutorial on integrating ODEs in MATLAB and Python
# [[Software_tutorial/Integration of ODEs|Integrating ODEs]]: a tutorial on integrating ODEs in MATLAB and Python
# [[Software_tutorial/Least squares modelling (linear regression)|Least squares modelling]]: a tutorial on (linear regression) in MATLAB and Python
# [[Software_tutorial/Least squares modelling (linear regression)|Least squares modelling]]: a tutorial on (linear regression) in MATLAB and Python
# [[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: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 has recently finished (February 2012).
  -->
  -->


* Want tutorials on other topics: please [mailto:kevin.dunn@mcmaster.ca email me]
== R-related resources ==
<!-- == Need some more help? ==


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.twotorials.com/ The two-minute tutorials] on many R-related aspects
<!--
* 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)

  1. About the course software
  2. Software installation
  3. Getting started
  4. Reading data into R
  5. Basic data manipulation in R
  6. Basic plots in R
  7. Plots with multiple series, colour, and legends
  8. Histograms
  9. Annotating plots: grid lines, arrows, lines, and identifying interesting points
  10. Dealing with factors (categorical variables)
  11. Calculating statistics from a data sample
  12. Dealing with distributions
  13. Extending R with packages
  14. Programming in R: loops and flow control
  15. Vectors and matrices
  16. Building a least squares model in R
  17. Extracting information from a linear model in R
  18. Testing a linear model in R
  19. Transformation of data in a linear model
  20. Investigating outliers, discrepancies and other influential points
  21. Linear models with multiple X-variables (MLR)
  22. Linear models with integer variables


  • Want tutorials on other topics: please email me

R-related resources

Not every aspect about R can be covered with our tutorial (above). Here are some additional resources.


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