Statistics for Fission-Track Thermochronology

  • Pieter VermeeschEmail author
Part of the Springer Textbooks in Earth Sciences, Geography and Environment book series (STEGE)


This chapter introduces statistical tools to extract geologically meaningful information from fission-track (FT) data using both the external detector and LA-ICP-MS methods. The spontaneous fission of 238U is a Poisson process resulting in large single-grain age uncertainties. To overcome this imprecision, it is nearly always necessary to analyse multiple grains per sample. The degree to which the analytical uncertainties can explain the observed scatter of the single-grain data can be visually assessed on a radial plot and objectively quantified by a chi-square test. For sufficiently low values of the chi-square statistic (or sufficiently high p values), the pooled age of all the grains gives a suitable description of the underlying ‘true’ age population. Samples may fail the chi-square test for several reasons. A first possibility is that the true age population does not consist of a single discrete age component, but is characterised by a continuous range of ages. In this case, a ‘random effects’ model can constrain the true age distribution using two parameters: the ‘central age’ and the ‘(over)dispersion’. A second reason why FT data sets might fail the chi-square test is if they are underlain by multimodal age distributions. Such distributions may consist of discrete age components, continuous age distributions, or a combination of the two. Formalised statistical tests such as chi-square can be useful in preventing overfitting of relatively small data sets. However, they should be used with caution when applied to large data sets (including length measurements) which generate sufficient statistical ‘power’ to reject any simple yet geologically plausible hypothesis.



The author would like to thank reviewers Rex Galbraith, Mauricio Bermúdez and editors Marco Malusà and Paul Fitzgerald for detailed feedback. The mica counts of Fig. 6.1 were performed by Yuntao Tian.


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© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.London Geochronology Centre, University College LondonLondonUK

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