  Prior beliefs are central to Bayesian accounts of cognition, but many of
these accounts do not directly measure priors. More specifically, initial
states of belief heavily influence how new information is assumed to be
utilized when updating a particular model. Despite this, prior and posterior
beliefs are either inferred from sequential participant actions or elicited
through impoverished means. We had participants play a version of the game
"Plinko", to first elicit individual participant priors in a theoretically
agnostic manner. Subsequent learning and updating of participant beliefs was
then directly measured. We show that participants hold a variety of priors that
cluster around prototypical probability distributions that in turn influence
learning. In follow-up experiments we show that participant priors are stable
over time and that the ability to update beliefs is influenced by a simple
environmental manipulation (i.e. a short break). This data reveals the
importance of directly measuring participant beliefs rather than assuming or
inferring them as has been widely done in the literature to date. The Plinko
game provides a flexible and fecund means for examining statistical learning
and mental model updating.
