R for Beginners

Bangalore, 2-6 August 2010

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Objectives

1. Learn to use R for the management, description, analysis and visualisation of ecological data.
2. Learn best principles of data exploration, analysis and visualisation.

Before the Course...

Download and install R:
Go to: www.r-project.org 
click: download R, and choose site
Choose OS and install R

Download and read the following:
R for Beginners
R tips sheet

Course Schedule

Day 1 - Introduction to R, philosophy and basic ideas

Class 1. Introduction to R                                              (ppt | R code)

Class 2. Tour of R                                                         (ppt)

Class 3. First R session, guided                                      (ppt | R code)

Class 4. Subsets and Data Management                         (R code | squid )


Exercises:

  Exercises 1     data: ISIT  .txt    deer    

  Exercises 2     data: Birdflu.txt   Birdflu.xls

Day 2 - Exploring and Visualising Data

Class 5. Useful Functions (apply etc).                                   data: vegetation2, deer

  Exercises 5 | data: temp.xls


Class 6. Basic Graphics                                                       data: vegetation2

  Exercises 6 | data: amphib road kill


  The Visual Display of Quantitative Information             pdf


Class 7. Advanced Graphics                                                 data: birdflucases birdfludeaths RIK2 owls deer
                                                                                                   teethnitrogen
  Exercises 7 | data: birdfludeaths vegetation2 codparasite owls

  More graphics resources: palettes colour1 colour2 colour3 plot.math plot.math2

Day 3 - Statistical Analysis of Data

  A Protocol for Data Exploration to Avoid Common Mistakes     (pdf | article)

Class 8. Classical Tests                                                     data: twosample, skewdata

Class 9. Linear Regression

Class 9b. Multiple Linear Regression                                                            

Class 10. ANOVA                                                              data: growth

Class 11. Generalized Linear Models                                   data: clusters, sexratio, isolation, species, germination

Day 4 - Advanced Statistics & Programming in R

Class 12. Writing Functions

  Exercises 12 | data: species.counts

Class 13. If, For, While, Repeat                                          data: indices

  Exercises 13

Class 14. Random Sampling & Numbers

  Exercises 14

Day 5 - Specialised Topics in R

Class 15. Mixed Effects Models                                           data: seedling, fruit | Bolker article

 

Resources

text editors

a list of text editors for Windows, Mac and Linux

books

Ben Bolker Ecological Models and Data in R
Mick Crawley The R Book
Venables & Ripley Modern Applied Statistics in S-Plus
Andrew Gelman & Jennifer Hill Hierarchical Models
Alain Zuur et al A Beginner's Guide to R

graphics

Edward Tufte: The Visual Display of Quantitative Information, Envisioning Information, Beautiful Evidence
Murrell R Graphics
Bill Cleveland The Elements of Graphing Data, Visualizing Data
R Graph Gallery
Gallery of Data Visualisation
dot plots
simple graphs
ggplot2

websites

R project
R help
R wiki
R Introduccion (en linea, ingles)

Ecology and Epidemiology in R

Burns stats     StatsRus

spreadsheets

spreadsheet addiction
why does Excel suck so much?

blogs

Andrew Gelman
Methods in Ecology and evolution Journal
badscience

programming

online programming R resources

Braun W.J., Murdoch D.J. A First Course in Statistical Programming with R
Phil Spector Data Manipulation with R

Peter Hurd

scientific notation