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*Universe*, Volume 9, Issue 3 (March 2023) – 44 articles

**Cover Story**(view full-size image): The Bayesian evidence is a key tool in model selection, allowing a comparison of models with different numbers of parameters. Its use in the analysis of cosmological models has been limited by difficulties in calculating it, with current numerical algorithms requiring supercomputers. In this paper, we give exact formulae for the Bayesian evidence in the case of Gaussian likelihoods with arbitrary correlations and top-hat priors, and approximate formulae for the case of likelihood distributions with leading non-Gaussianities (skewness and kurtosis). We find that the analytical results have slightly lower precision than the thermodynamic numerical integration, while still being good enough to be useful. The main advantage is that the computational time is reduced by many orders of magnitude, thanks to the analytical expressions. View this paper

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