Watching this resources will notify you when proposed changes or new versions are created so you can keep track of improvements that have been made.
Favoriting this resource allows you to save it in the “My Resources” tab of your account. There, you can easily access this resource later when you’re ready to customize it or assign it to your students.
The theory of probability is a representation of probabilistic concepts in formal terms—that is, in terms that can be considered separately from their meaning. These formal terms are manipulated by the rules of mathematics and logic, and any results are interpreted or translated back into the problem domain.
There have been at least two successful attempts to formalize probability, namely the Kolmogorov formulation and the Cox formulation. In Kolmogorov's formulation, sets are interpreted as events and probability itself as a measure on a class of sets. In Cox's theorem, probability is taken as a primitive (that is, not further analyzed), and the emphasis is on constructing a consistent assignment of probability values to propositions. In both cases, the rules of probability are the same, except for technical details.
The addition law of probability (aka addition rule or sum rule), states that the probability that A or B will happen is the sum of the probabilities that A will happen and that B will happen, minus the probability that both A and B will happen. The addition rule can be visualized by the equation in .
Consider the following example. When drawing one card out of a deck of 52 playing cards, what is the probability of getting a face card (king, queen, or jack) or a heart? Let H denote drawing a heart and F denote drawing a face card. Since there are 13 hearts and a total of 12 face cards (3 of each suit - spades, hearts, diamonds and clubs), but only 3 face cards of hearts, we obtain:
The reason for subtracting the last term is that otherwise we would be counting the middle section twice (in case A and B overlap). If A and B are mutually exclusive (also called disjoint, since they do not overlap), then the latter probability is zero.
Addition Rule for Disjoint Events
Therefore, when A and B are mutually exclusive, then P(A ∩ B) = 0, and
P(A ∪ B) = P(A) + P(B), when A ∩ B = ∅.
The symbol ∅ represents the empty set, which means that in this case A and B do not have any elements in common (do not overlap).
P(A or B) is the sum of the P(A) and P(B), minus the P(A), P(A or B) is the sum of the P(A) and P(B), minus the P(A and B), P(A or B) is the sum of the P(A) and P(B), or P(A or B) is the sum of the P(A and B) minus P(A) and P(B)