  The aim of this paper is to show that the concept of probability is best
understood by dividing this concept into two different types of probability,
namely physical probability and analogical probability. Loosely speaking, a
physical probability is a probability that applies to the outcomes of an
experiment that have been judged as being equally likely on the basis of
physical symmetry. Physical probabilities are arguably in some sense
'objective' and possess all the standard properties of the concept of
probability. On the other hand, an analogical probability is defined by making
an analogy between the uncertainty surrounding an event of interest and the
uncertainty surrounding an event that has a physical probability. Analogical
probabilities are undeniably subjective probabilities and are not obliged to
have all the standard mathematical properties possessed by physical
probabilities, e.g. they may not have the property of additivity or obey the
standard definition of conditional probability. Nevertheless, analogical
probabilities have extra properties, which are not possessed by physical
probabilities, that assist in their direct elicitation, general derivation,
comparison and justification. More specifically, these properties facilitate
the application of analogical probability to real-world problems that can not
be adequately resolved by using only physical probability, e.g. probabilistic
inference about hypotheses on the basis of observed data. Careful definitions
are given of the concepts that are introduced and, where appropriate, examples
of the application of these concepts are presented for additional clarity.
