For the test trials, the probability that movement regime is m conditioned on activity y in delay can be calculated by Bayes' rule illustrated in (4).

Bayes' rule with Gaussian hypothesis was utilized to estimate the target direction quantitatively.

But appropriate application of

Bayes' rule, far from preempting the

At the end of the first period, having observed the amount of money demanded (but not the random shock), the central bank updates beliefs about them using

Bayes' rule.

We began with the procedures used by Grether (1980) and El-Carnal and Grether (1995) in which subjects guessed from which cup a sample was drawn, and could maximize expected earnings by making decisions in accordance with

Bayes' Rule. Next, we introduced a simple insurance market in which subjects could purchase a policy that fully reimbursed them for the penalty assessed when an incorrect decision was made.

These decisions were consistent with

Bayes' rule and with private information.

As this announcement does not occur on the equilibrium path, this (admittedly strange) belief does not contradict the assumption that on the equilibrium path beliefs are updated by

Bayes' rule. With these beliefs the private sector always expects inflation to be given by the discretionary rule, regardless of announcement.

Further, since [q.sub.a] = [q.sub.b], it is immediate from

Bayes' Rule that the posterior belief associated with [S.sub.i] = 1 is simply equal to the prior belief [Pi].

Unless we track the changes in our confidence by using

Bayes' rule to update inductive probabilities, all unrefuted hypotheses remain equally trustworthy and equally testworthy.

In order to apply Bayesian analysis to fMRI data and make inference to the parameters that we are interested in, like finding the change points in the dataset, we need to set up a probability model for the data and find a prior to apply

Bayes' Rule.

But no one promised that applying

Bayes' rule would be costless.

Thus, if an employee goes to her for advice, she must use

Bayes' rule to determine the probability that the employee's problem is big or small.