Using R to enhance numeracy in geography: some pros and cons
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The document discusses the use of R programming to enhance numeracy in geography, highlighting its advantages such as being intuitive, free, and supported by a large user community, along with its strong graphical capabilities. It also addresses potential drawbacks, including challenges for non-native speakers and limitations in handling complex data structures. The integration of R into academic curricula and available resources for teaching R is also emphasized.
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Using R to enhance numeracy in geography: some pros and cons
- 1. Using R to enhance numeracyin geography: some pros and cons Rich Harriswww.social-statistic.org@socstatisticsUsing R to enhance numeracy in geography: some pros and cons by Richard Harris / University of Bristol is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
- 2. From my office doorA society in which our lives and choices are enriched by an understanding of statisticsgetstats.org.ukA little idealistic but…
- 3. The Crisis of NumeracyTo unravel the complexities of society requires a highly skilled research base, equipped with suitable tools and techniques, most notably advanced quantitative methods […] Yet there are persistent concerns that the UK lacks the critical mass to satisfy such demand. ESRC document (2011)
- 4. How can R help?Broadly intuitiveStrong focus on graphicsIt has in build good practiceIt’s free and cross-platformhttp://cran.r-project.org/Extendable and customisableLibraries for mapping, spatial statistics, spatial regression, geostatistics, etc.Large user community
- 5. It’s not esoteric!“R is used at the world’s largest technology companies (including Google, Microsoft and Facebook), the largest pharmaceutical companies (including Johnson & Johnson, Merck, and Pfizer), and at hundreds of other companies. It’s used in statistics classes at universities around the world and be statistical researchers to try new techniques and algorithms”Adler (2010)
- 6. Example graphic made in R:Guardian league table rankings by University
- 7. Reading data into R
- 9. Pseudo-code &Simple descriptive statistics
- 13. Mapping(this is where it gets interesting!)
- 14. Some prosCommand lineFaster, pedagogically superior (learning by doing, no dumb button pushing!)Keeps a clear log of what’s been triedWhich could be re-run as a scriptGraphics are of publishable quality and easy to customiseInteractiveExtensive help documentationRealistic exposure to research level computing environment
- 15. Some consRisk of automated copying by scriptsI always create individualised data for assessed project workPigeon English is hard for overseas studentsThere is native language supportWill often allow you to make errors!Isn’t a software package that will mean much to most employersThough the skill of statistical computing may be more credible
- 16. In general“R is very good at plotting graphics, analyzing data, and fitting statistical models using data that fits in the computer’s memory. It’s not good at storing data in complicated structures, efficiently querying data, or working with data that doesn’t fit in the computer’s memory.”Adler (2010)
- 17. Integration into the curriculum at Bristol School of Geographical Sciences
- 18. ResourcesBooks & Manuals for Rhttp://cran.r-project.org/Using R for Introductory Statistics (Verzani, 2004)Statistics: An Introduction Using R (Crawley, 2005)R in a Nutshell (Adler, 2009)The UseR serieshttp://www.springer.com/series/6991Integration of R with Excelhttp://www.statconn.com/https://stat.ethz.ch/mailman/listinfo/r-sig-teachingSpecial Interest Group (SIG) on teaching statistics with R. One particular focus of the SIG is to provide helpful support to instructors new to R who are teaching introductory statistics courses populated with students with little experience in statistics, statistical software, and command line interfaces.
- 19. And of course…Workshop tomorrow13.30 – 15.00 (Horton B)Teaching materialwww.social-statistics.orgFrom late 2011 onwards