  Order effects occur when judgments about a hypothesis's probability given a
sequence of information do not equal the probability of the same hypothesis
when the information is reversed. Different experiments have been performed in
the literature that supports evidence of order effects.
  We proposed a Bayesian update model for order effects where each question can
be thought of as a mini-experiment where the respondents reflect on their
beliefs. We showed that order effects appear, and they have a simple cognitive
explanation: the respondent's prior belief that two questions are correlated.
  The proposed Bayesian model allows us to make several predictions: (1) we
found certain conditions on the priors that limit the existence of order
effects; (2) we show that, for our model, the QQ equality is not necessarily
satisfied (due to symmetry assumptions); and (3) the proposed Bayesian model
has the advantage of possessing fewer parameters than its quantum counterpart.
