- Course outline
- Overview
- Linear and logistic regression models
- Exploratory analysis
- Linear geostatistical models
- Geostatistical design
- Binomial geostatistical models
- Prevalence mapping
- Q&A, closing remarks
- Introduction to R (slides and code)
- Introduction to R (code only)
- Introduction to R (solutions to exercises)
- Fitting linear and generalized linear models(slides and code)
- Fitting linear and generalized linear models(code only)
- Fitting linear and generalized linear models (solutions to exercises)
- Map-making in R (slides and code)
- Map-making in R (code only)
- Map-making in R (solutions to exercises)
- Linear geostatistical models (exercises and code)
- Linear geostatistical models (solutions to exercises)
- Geostatistical prediction (exercises and code)
- Geostatistical prediction(code only)
- Geostatistical prediction (solutions to exercises)
- Binomial geostatistical models (slides and code)
- Binomial geostatistical models(code only)
- Binomial geostatistical models (solutions to exercises)
- Prevalence mapping (slides and code)
- Prevalence mapping (code only)
- Prevalence mapping (solutions to exercises)
- IntrotoRforMac
- IntrotoRforPC
- examplesession.R
- For a more detailed set of notes by Bill Venables and David Smith, click here
### Data-sets

- README.txt
- cholera_explain.txt
- cholera.deaths.txt
- cholera.pumps.txt
- Loaloa.explain.txt
- Loaloa.txt
- LiberiaRemoData.csv
- LiberiaRemo_explain.txt
- elevation.csv
- elevation_explain.txt
- lead2000.csv
- lead2000_explain.txt
- Galicia_boundary.csv
- Introduction to the geoR package

### Information on R packages

http://www.lancs.ac.uk/staff/diggle/

Last Modified: 27/10/2014