Basic terms relative to Probability Theory:

Event:	One of a number of potential occurrences, for example, in a situation in which several different outcomes are possible: “rain”, “snow”, “rain or snow”, “rain and snow”, etc. – a family of events consists of all the events of interest in that given situation.
Probabilities:	For such a situation containing a family of events, say event A, event B, event C, and so on, “probability” is a number, for example, 0.3, assigned to each of these events which captures or signifies the estimated or actual degree of certainty about the occurrence of the particular event. 0.3, in this instance, might represent that there is a 30% chance of rain for the day (or for the morning or afternoon, etc).
Relations:	Of key importance are the relations which exist between the events identified or specified – are the events disjoint (mutually exclusive), i.e., that they cannot co-occur? For example, in the case of the risk of a machine failing there are several reasons – Reason 1 and Reason 2 – and it is determined that the machine cannot fail for both reasons, only because of either circumstance.
	and
Coherence:	This is when the likelihood judgements described do not violate rules of Probability Theory such as Additivity, that is, the likelihood judgements treat each specified event as mutually exclusive – that the numbers (numerical assignments) ‘add up’. For example, if a weather forecaster offered the statement about the chance of “rain” or “no rain” (call it “fine”) for to-morrow with the former given 60% or .6 and the latter 55% or .55 these assignments do not satisfy additivity and the judgement would be said to be incoherent.