Table 5. Bayes factors for the duration estimates of Experiments 1a-3.

Experiment	Bayes Factor
1a	68.2
1b	48.5
1c – Retrospective Judgments	10.3
1c – Prospective Judgments	11.7
2– Retrospective Judgments	28.9
2– Prospective Judgments	57.2
3	127.9

The Bayes factor is the probability of the observed data under the null hypothesis divided by the probability of the data under the distribution of alternative hypotheses specified by the Zellner-Siow g prior. Values greater than 1 indicate support for the null hypothesis that there is no effect of temporal structure on duration estimates. Values greater than 10 are often labelled “strong” evidence for the null; values greater than 30 are “very strong” evidence [48].