Here are the opening lines of Wikipedia’s excellent entry for the Bayesian concept of prior probability:

… a prior probability distribution, often called simply the prior, of an uncertain quantity p (for example, suppose p is the proportion of voters who will vote for the politician named Smith in a future election) is the probability distribution that would express one’s uncertainty about p before the “data” (for example, an opinion poll) is taken into account. It is meant to attribute uncertainty rather than randomness to the uncertain quantity.

In other words, the “prior” is a value that measures one’s level of uncertainty about a given event. Also, notice that by openly acknowledging one’s uncertainty about events in the world, the prior serves as a useful starting point (not an end point) towards knowledge.

In future posts, we will explain the process of “updating” one’s priors and how Bayesian methods might apply to law and the legal process.

Bonus links:

• DATING FOR BAYESIANS: Here’s How To Use Statistics To Improve Your Love Life (businessinsider.com)
• Fun with Bayesian Priors (jliszka.github.io)
• What is Bayesian Statistics: A basic worked example (hilbertthm90.wordpress.com)