Statistical research

I’m not sure that I do statistics research in any way a proper statistician would recognise; but that’s perhaps ok as I’m looking to write papers aimed at biologists rather than statisticians. I’m trying to highlight useful corners of statistical theory that most textbooks overlook. That said, its surprising however how often as we look at the literature on a problem we find that a little bit of new analysis needs to be done to help round off the story a little. I do really enjoy getting my head around little statistical problems. I’m helped in this by some great collaborators: Markus Neuhäuser in Germany, Guy Beauchamp in Canada, and most recently Arthur Pewsey in Spain. My interest in experimental design with Nick Colegrave also interlinks with this work.


Find a list of some of our papers below:

Ruxton GD, Rey D, Neuhauser M (2010) Comparing samples with large numbers of zeros. Animal Behaviour 80: 937-940

Ruxton GD, Neuhauser M (2010) Good practice in testing association in contingency tables. Behavioral Ecology and Sociobiology 64, 1505-1513

Ruxton GD, Neuhauser M (2010) When should we use one-tailed hypothesis testing? Methods in Ecology and Evolution 1, 114-117

Neuhauser M, Ruxton GD (2009) Round your numbers in rank tests: exact and asymptotic inference and ties. Behavioral Ecology & Sociobiology 64, 297-303

Neuhauser M, Ruxton GD (2010) Distribution-free two-sample comparisons in the case of heterogeneous variances. Behavioral Ecology & Sociobiology 63, 617-623

Ruxton GD, Beuachamp N (2008) Some suggestions about appropriate use of the Kruskal-Wallis test. Animal Behaviour 76, 1083-1087

Ruxton GD, Beauchamp G (2008) Time for some a priori thinking about post hoc testing. Behavioral Ecology 19, 690-693

Colegrave N, Ruxton GD (2003) Confidence intervals are a more useful complement to non-significant tests than are power calculations. Behavioral Ecology 14, 446-447