- The outcome of Bayesian analysis is a modification of the
**prior**(the probability of an event that is known before the analysis) which produces the**posterior**(the probability of an event given certain conditions and dependent upon the prior). - Bayesian analysis requires three pieces of information: the prior and two conditional probabilities (a true positive and a false positive outcome).
- If the two conditional probabilities are equal, the prior is unmodified and equals the posterior. This is because
*the result of the test is uncorrelated with the outcome*. - The degree to which the prior is modified can be described by the concept of
**differential pressure**, i.e. the relative difference between the two conditional probabilities. The process of changing the prior due to differential pressure is known as**selective attrition**. - People use spatial intuition to grasp numbers. Teachers can use this and the idea of natural frequencies to their advantage to teach difficult concepts.
- Related to number 5, the way in which given information is presented in a word problem (e.g. percentages vs. ratios) will affect the percentage of correct scores.

*a priori*and

*a posteriori*knowledge?