Your SlideShare is downloading. ×
Using R to enhance numeracy in geography: some pros and cons
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Introducing the official SlideShare app

Stunning, full-screen experience for iPhone and Android

Text the download link to your phone

Standard text messaging rates apply

Using R to enhance numeracy in geography: some pros and cons

1,256
views

Published on

A short presentation for the 2011 Geography, Earth and Environmental Sciences conference (Teaching and Learning for GEES Students, Birmingham) exploring how R might help improve the statistical …

A short presentation for the 2011 Geography, Earth and Environmental Sciences conference (Teaching and Learning for GEES Students, Birmingham) exploring how R might help improve the statistical numeracy of undergraduate students.

Published in: Education, Technology

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
1,256
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
16
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Using R to enhance numeracyin geography: some pros and cons
    Rich Harriswww.social-statistic.org@socstatistics
    Using 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 door
    A society in which our lives and choices are enriched by an understanding of statistics
    getstats.org.uk
    A little idealistic but…
  • 3. The Crisis of Numeracy
    To 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 intuitive
    Strong focus on graphics
    It has in build good practice
    It’s free and cross-platform
    http://cran.r-project.org/
    Extendable and customisable
    Libraries 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
  • 8. Exploring the data
  • 9. Pseudo-code &Simple descriptive statistics
  • 10. Manipulating the data
  • 11. Inferential statistics
  • 12. Relational statistics
  • 13. Mapping(this is where it gets interesting!)
  • 14. Some pros
    Command line
    Faster, pedagogically superior (learning by doing, no dumb button pushing!)
    Keeps a clear log of what’s been tried
    Which could be re-run as a script
    Graphics are of publishable quality and easy to customise
    Interactive
    Extensive help documentation
    Realistic exposure to research level computing environment
  • 15. Some cons
    Risk of automated copying by scripts
    I always create individualised data for assessed project work
    Pigeon English is hard for overseas students
    There is native language support
    Will often allow you to make errors!
    Isn’t a software package that will mean much to most employers
    Though 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. Resources
    Books & Manuals for R
    http://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 series
    http://www.springer.com/series/6991
    Integration of R with Excel
    http://www.statconn.com/
    https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
    Special 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 tomorrow
    13.30 – 15.00 (Horton B)
    Teaching material
    www.social-statistics.org
    From late 2011 onwards