Confirmation bias is when we unintentionally only seek out evidence or take notice of results that reinforce our existing views. With traditional statistics this might lead us not to publish results that we think are wrong, perhaps even removing data points that we feel must have been errors of some kind. In Bayesian statistics confirmation bias can cause even more problems, as the choice of prior probability is effectively one's own beliefs encoded as a probability and hence the output of the process, the posterior probability, may simply reflect one's existing prejudices.
Also used in hcistats2e: Chap. 5: page 64; Chap. 7: pages 74, 85, 86; Chap. 8: page 87
Used in glossary entries: Bayesian statistics, encoding (belief) as probability, posterior distribution, prior distribution, traditional statistics
