GEOSTAT courses

Upcoming events

See all upcoming training courses.

To receive a notice about the GEOSTAT summer school, please subscribe to the R-sig-geo mailing list, or send an e-mail to the course organizers.

Regular courses/meetings

• Aarhus Universiteit, DK: Courses from the Research Unit of Bioinformatics, Genetics and Statistics;
• Academy for PhD Training in Statistics, UK
• Arizona State University, USA: The GeoDa Center for Geospatial Analysis and Computation e-learning courses;
• Bioconductor workshops;
• CSISS, University of California, Santa Barbara: Advanced Spatial Analysis workshops;
• Copenhagen University, DK: Hands-on training courses on spatial ecological modeling using R, GRASS and other open source tools;
• The University of Manchester, UK: CCSR Short Courses;
• University of Muenster, DE: IfGI Spring school;
• Global GIS academy e-learning courses;
• ISRIC - World Soil Information, Wageningen, NL: ISRIC training and education courses;
• Lancaster University, UK: Short courses: R;
• Mango Solutions, UK: The R Language courses;
• Imperial college London, UK: Introduction to R courses;
• ITC, Enschede, NL: Geostatistics and Open-Source Statistical Computing (distance education course);
• useR! conferences (includes also workshop and training sessions);
• NPS's web-inars on using R for monitoring natural resources;
• University of Oregon, Dept. Geography, USA: Geographic Data Analysis Using R courses;
• Wageningen University and Research, NL: PE&RC Postgraduate Courses;

People in Academia running courses on spatial data analysis with R

• Roger Bivand, NHH, Bergen, Norwey;
• Gilberto Câmara, National Institute for Space Research, Brasil;
• Bendix Carstensen, Department of Biostatistics, University of Copenhagen, Denmark;
• Ole Christensen, Aarhus Universitet, Denmark;
• Peter Dalgaard, University of Copenhagen, Denmark;
• Jerome H. Friedman, Standford University, USA;
• John Fox, McMaster University, Hamilton, Canada;
• Paul Galpern, University of Manitoba, Winnipeg, Canada;
• Paul Geissler, consultat, USA;
• Trevor Hastie, Standford University, USA;
• Robert Hijmans, University of California, Davis, USA;
• Gerard B.M. Heuvelink, Wageningen University and Research, NA;
• Matthew C. Keller, University of Colorado, Boulder, USA;
• Petra Kuhnert, CSIRO, Australia;
• Michael Lachmann, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany;
• Edzer Pebesma, Universität in Münster, Germany;
• David G. Rossiter, ITC, Enschede, NL;
• Ashton Shortridge; Michigan State University, East Lansing, MI, USAEast Lansing, MI
• Martin Theus, University of Augsburg, Germany;

Teach-your-self literature

1. Beginners-level:
   • Beaudette, D., 2009. Open Source Software Tools for Soil Scientists, University of California at Davis.
   • Braun, W.J., Murdoch, 2008. A First Course in Statistical Programming with R. Cambridge University Press, Cambridge, 174 p. ISBN 9780521694247
   • Crawley, M.J., 2005. Statistics: An Introduction using R. John Wiley & Sons, Ltd. ISBN 0470022973
   • Everitt, B.S., Hothorn, T., 2006. HSAUR: A Handbook of Statistical Analyses Using R. Chapman & Hall/CRC, 325 p.
   • Kabacoff, R.I., 2011. R in Action: Data Analysis and Graphics with R. Manning publications, 472 p. ISBN 9781935182399
   • Kuhnert, P., Venables, W.N., 2005. An Introduction to R: Software for Statistical Modelling & Computing. CSIRO Canberra, Australia, 362 p.
   • R Development Core Team, 2008. An Introduction to R. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3900051127
   • Venables, W.N., Smith, D.M., R Development Core Team, 2004. An Introduction to R. Network Theory Ltd, 156 p. ISBN 0954161742
   • see also: Books on R
   • USGS R course materials (teach yourself)
2. Spatial data analysis/visualization in R:
   • Baddeley, A., 2008. Analysing spatial point patterns in R. CSIRO Canberra, Australia.
   • Bivand, R., Pebesma, E., Rubio, V., 2008. Applied Spatial Data Analysis with R. Use R Series, 400 p. Springer, Heidelberg, p. 378.
   • Diggle, P.J., Ribeiro Jr, P.J., 2006. Model-based Geostatistics. Springer Series in Statistics, 230 p.
   • Reimann, C., Filzmoser, P., Garrett, R., Dutter, R., 2008. Statistical Data Analysis Explained Applied Environmental Statistics with R. Wiley, Chichester, 337 p.
   • Theus, M., Urbanek, S., 2008. Interactive Graphics for Data Analysis: Principles and Examples. CRC Press, 277 p.