Course Aim: To introduce the basic statistical concepts relevant to environmental science and to provide experience in the correct use and interpretation of the various statistical methods currently used in the analysis of weather/climate observed and model simulated data.
Practical Exercises Each topic covered in the lectures will be followed by exercises analyzing real data in practical computing classes using R statistical software.
Prerequisites Minimal statistical knowledge but some basic mathematics and computer skills will be assumed.
``Some people hate the very name of statistics but I find them full of beauty and interest. Whenever they are not brutalized, but delicately handled by the higher methods, and are warily interpreted, their power of dealing with complicated phenomena is extraordinary.''
- Sir Francis Galton 1
The development of this course has benefited from many stimulating discussions with colleagues and students over the past few years. In particular, I wish to thank Nils Gunnar Kvamsto, Rasmus Benestad, and students at the University of Bergen for their helpful comments on the first version of this course.
In addition, I would like to thank my kind colleagues in the Climate Analysis Group at the University of Reading, who took the time to read the whole of these lecture notes and provided invaluable comments (Chris Ferro, Abdel Hannachi, Sergio Pezzulli, Barbara Casati, and Matt Sapiano).
Despite all this feedback, there is a non-zero probability that these notes might still contain some mistakes - if you find any mistakes or have any suggestions for improvements then please let me know by sending an email to D.B.Stephenson@reading.ac.uk.