Using Software in Teaching Statistics

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Using Software in Teaching Statistics

• Damon Berridge, Centre for Applied Statistics,
  Dept of Mathematics Statistics
• d.berridge_at_lancaster.ac.uk
• ESRC NCRM Meeting Training the Trainers,
  London, 4 June 2007

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Acknowledgement

• This presentation is based on a set of Powerpoint
  slides Using Open Source Software to Teach
  Mathematical Statistics by Douglas M. Bates,
  University of Wisconsin-Madison
• http//www.stat.wisc.edu/bates/JSM2001.pdf

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Outline

• Discussion of general issues
• Introduction to R
• Obtaining installing R
• Examples
• Useful resources
• Concluding remarks

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Discussion of general issues

• It is common to use some statistical software in
  teaching statistics to social scientists.
• Software in statistics courses for social
  scientists must have a simple interface for it to
  be useful.
• Is it important that use of computing system be
  integrated with lectures and text?

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Linking the computing to the text

• Two ways of achieving this
• Write a text that is tied to specific software
  and illustrates the use of that software, e.g.
  CAS course on GLMs.
• Adopt a conventional text but provide examples
  from text in computing system, e.g. CAS course on
  Duration Analysis.
• Alternatively
• Write self-standing material that is not tied to
  specific software, e.g. LEMMA.

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Advantages of Open Source software

• No licence fees or management of licences.
• Software can be installed on all departmental
  PCs.
• Staff and students can install software on their
  own laptops without charge (and without violating
  licences).
• Open Source projects encourage contributions from
  users so extensions are easier.

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Introduction to R

• A number of CAS methodology courses use Open
  Source software such as R.
• R is an Open Source project based largely on
  interactive programming language S.
• Initially developed by Ihaka Gentleman at
  University of Auckland in 1996.

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Introduction to R contd.

• R is now developed and maintained by a
  widely-dispersed, international group of
  volunteers from academia and industry.
• R operates through web sites, archives, e-mail
  lists, etc. (see Useful Resources).

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What is R?

• An Open Source implementation of programming
  language S.
• A language and environment for data analysis and
  graphics.
• A means of technology transfer through packages,
  e.g. SABRE in R.

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What is R? contd.

• A flexible data exchange mechanism accessing
• text files and saved R workspaces
• S-PLUS data objects, SAS XPORT datasets, SPSS
  saved datasets, Minitab worksheets, etc.

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How do I get R?

• Informational web site
• http//www.r-project.org/
• CRAN the Comprehensive R Archive Network
• Primary CRAN site
• http//cran.r-project.org/
• Mirror sites, e.g.
• http//cran.uk.r-project.org/
• New releases occur frequently be prepared to
  re-install!

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Installing R in Windows

• Simple procedure download and run installer
  R-2.5.0-win32.exe
• CRAN sites are available for installing R on
  other platforms, e.g. Macintosh, Linux, Unix,
  etc.

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Example 1 Web-based resources
Registration required example sessions available
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Example 2 Support material

• Course notes available for downloading from
• http//www.cas.lancs.ac.uk/short_courses/coursemat
  erials.html
• Audio, slides and demos available at
• http//www.cas.lancs.ac.uk/e-learning/index.php
• are based on the notes.

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Useful resources

• Web site http//www.r-project.org/ and CRAN.
• FAQ list at http//cran.r-project.org/doc/FAQ/
• is a good source of information.
• Manuals in documentation directory
• http//cran.r-project.org/doc/manuals
• See especially R-intro.pdf and R-data.pdf.
• Paper Using the R statistical computing
  environment to teach social statistics courses
  by Fox Andersen, Dept of Sociology, McMaster
  University
• http//socserv.mcmaster.ca/jfox/Teaching-with-R.pd
  f