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In probability theory, an event is a subset of outcomes of an experiment (a subset of the sample space) to which a probability is assigned. [1] A single outcome may be an element of many different events, [2] and different events in an experiment are usually not equally likely, since they may include very different groups of outcomes. [3]
For example, in the game of bridge, the probability that a player will be dealt 13 cards of the same suit is extremely low (Littlewood calculates it as ). While such a deal might seem miraculous, if one estimates that 2 ⋅ 10 6 {\displaystyle 2\cdot 10^{6}} people in England each play an average of 30 bridge hands a week, it becomes quite ...
Let these events be called Event 2, Event 3, and so on. Event 1 is the event of person 1 having a birthday, which occurs with probability 1. This conjunction of events may be computed using conditional probability : the probability of Event 2 is 364 / 365 , as person 2 may have any birthday other than the birthday of person 1.
Probability is a measure of the likeliness that an event will occur. Probability is used to quantify an attitude of mind towards some proposition whose truth is not certain. The proposition of interest is usually of the form "A specific event will occur." The attitude of mind is of the form "How certain is it that the event will occur?"
The event that contains all possible outcomes of an experiment is its sample space. A single outcome can be a part of many different events. [4] Typically, when the sample space is finite, any subset of the sample space is an event (that is, all elements of the power set of the sample space are defined as events
In probability theory and statistics, where the variable p is the probability in favor of a binary event, and the probability against the event is therefore 1-p, "the odds" of the event are the quotient of the two, or . That value may be regarded as the relative probability the event will happen, expressed as a fraction (if it is less than 1 ...
This is the same as saying that the probability of event {1,2,3,4,6} is 5/6. This event encompasses the possibility of any number except five being rolled. The mutually exclusive event {5} has a probability of 1/6, and the event {1,2,3,4,5,6} has a probability of 1, that is, absolute certainty.
Finally, there is a need to specify each event's likelihood of happening; this is done using the probability measure function, P. Once an experiment is designed and established, ω from the sample space Ω, all the events in F {\displaystyle \scriptstyle {\mathcal {F}}} that contain the selected outcome ω (recall that each event is a subset of ...