1. Using Software in Teaching Statistics Damon Berridge, Centre for Applied Statistics, Dept of Mathematics & Statistics d.berridge@lancaster.ac.uk ESRC NCRM Meeting: Training the Trainers, London, 4 June 2007

2. 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

3. Outline Discussion of general issues Introduction to R Obtaining & installing R Examples Useful resources Concluding remarks

4. 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?

5. 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.

6. 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.

7. 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.

8. Introduction to R – cont’d. 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).

9. 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.

10. What is R? – cont’d. 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.

11. 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!

12. 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.

13. Example 1: Web-based resources Registration required; example sessions available

14. Example 2: Support material Course notes available for downloading from: http://www.cas.lancs.ac.uk/short_courses/coursematerials.html Audio, slides and demos available at: http://www.cas.lancs.ac.uk/e-learning/index.php are based on the notes.

15. Useful resources Web site http://www.r-project.org/ and CRAN. http://www.r-project.org/ FAQ list at http://cran.r-project.org/doc/FAQ/ 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.pdf