Safe anytime-valid inference (SAVI) provides measures of statistical evidence and certainty—
e-processes for testing and confidence sequences for estimation—that remain valid at all …

We develop a representation of a decision maker's uncertainty based on e-variables. Like
the Bayesian posterior, this e-posterior allows for making predictions against arbitrary loss …

The Bayes factor surface is a new way to present results from experimental searches for new
physics. Searches are regularly expressed in terms of phenomenological parameters–such …

A standard practice in statistical hypothesis testing is to mention the p-value alongside the
accept/reject decision. We show the advantages of mentioning an e-value instead. With p …

Determining an appropriate sample size is a critical element of study design, and the
method used to determine it should be consistent with the planned analysis. When the …

A standard practice in statistical hypothesis testing is to mention the P-value alongside the
accept/reject decision. We show the advantages of mentioning an e-value instead. With P …

We show how e-values simplify the design and the conduct of experiments. These e-values
form anytime-valid tests and confidence intervals that preserve type I error guarantee …

We develop the theory of hypothesis testing based on the e-value, a notion of evidence that,
unlike the p-value, allows for effortlessly combining results from several studies in the …

The Bayes factor, the data-based updating factor of the prior to posterior odds of two
hypotheses, is a natural measure of statistical evidence for one hypothesis over the other …

When testing a statistical hypothesis, is it legitimate to deliberate on the basis of initial data
about whether and how to collect further data? Game-theoretic probability's fundamental …