Many parameters used in rock engineering design are characterized using objectively measured data, although at early design stages there often may be insufficient data available (epistemic uncertainty) to define the parameter in question. In such instances, the design process could benefit from the use of Bayesian statistics where informative priors can be constructed from expert knowledge and then updated as further test data become available. In this paper we use small sample sizes of uniaxial compressive strength as an exemplar parameter that exhibits epistemic uncertainty to show how the Bayesian updating takes place. We then use the example of the analysis of rock spalling around an underground opening to show how the results of Bayesian analysis can be used to improve estimates of strength, leading to improved analysis of probability of failure.

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