  Multiple testing of a single hypothesis and testing multiple hypotheses are
usually done in terms of p-values. In this paper we replace p-values with their
natural competitor, e-values, which are closely related to betting, Bayes
factors, and likelihood ratios. We demonstrate that e-values are often
mathematically more tractable; in particular, in multiple testing of a single
hypothesis, e-values can be merged simply by averaging them. This allows us to
develop efficient procedures using e-values for testing multiple hypotheses.
