A statistical learning exercise based on a modified Rock-Paper-Scissors game

Paola Bortot, Stuart Coles

Abstract


The standard version of the game Rock-Paper-Scissors is interesting in terms of game theory, but less so in terms of Statistics. However, we show that with a small rule change it can be made into an interactive exercise for degree-level students of Statistics that leads to a Bayesian change-point model, for which the Gibbs sampler provides an intuitive method of inference. First, students play the game to generate the data. Second, they are encouraged to formulate a model that reflects their experience from having played the game. And third, they participate in the development of a suitable MCMC algorithm to fit the model.


Keywords


mathematics education; Bayesian Statistics; change-point analysis; Gibbs sampler; teaching

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References


Eckley, I.A., Fearnhead, P. and Killick, R., 2011. Analysis of changepoint models. In: D. Barber, A.T. Cemgil and S. Chiappa, eds. Bayesian Time Series Models, Cambridge: Cambridge University Press. pp.205-224.

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van den Nouweland, A., 2007. Rock-Paper-Scissors; A New and Elegant Proof. Economics Bulletin, 3(43), pp.1-6.

Walker, D. and Walker, G., 2004. The Official Rock Paper Scissors Strategy Guide. Touchstone.

Wang, Z., Xu, B. and Zhou, H.-J., 2014. Social cycling and conditional responses in the Rock-Paper-Scissors game. Scientific Reports, 4(5830). https://doi.org/10.1038/srep05830

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DOI: https://doi.org/10.21100/msor.v18i1.1032

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