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It depends on the events.

The answer is 0.5*(Total number of events - number of events with probability = 0.5)

That is, discount all events such that their probability (and that of their complement) is exactly a half.

Then half the remaining events will have probabilities that are greater than their complement's.

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Q: How often is the probability of the complement of an event less than the probability of the event itself?
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How can you state and illustrate the addition multiplication Theorem of Probability?

Addition Theorem The addition rule is a result used to determine the probability that event A or event B occurs or both occur. ; The result is often written as follows, using set notation: : ; where: : P(A) = probability that event A occurs : P(B) = probability that event B occurs : = probability that event A or event B occurs : = probability that event A and event B both occur ; For mutually exclusive events, that is events which cannot occur together: : = 0 ; The addition rule therefore reduces to : = P(A) + P(B) ; For independent events, that is events which have no influence on each other: : ; The addition rule therefore reduces to : ; Example ; Suppose we wish to find the probability of drawing either a king or a spade in a single draw from a pack of 52 playing cards. ; We define the events A = 'draw a king' and B = 'draw a spade' ; Since there are 4 kings in the pack and 13 spades, but 1 card is both a king and a spade, we have: : = 4/52 + 13/52 - 1/52 = 16/52 ; So, the probability of drawing either a king or a spade is 16/52 (= 4/13).MultiplicationTheorem The multiplication rule is a result used to determine the probability that two events, A and B, both occur. The multiplication rule follows from the definition of conditional probability. ; The result is often written as follows, using set notation: : ; where: : P(A) = probability that event A occurs : P(B) = probability that event B occurs : = probability that event A and event B occur : P(A | B) = the conditional probability that event A occurs given that event B has occurred already : P(B | A) = the conditional probability that event B occurs given that event A has occurred already ; For independent events, that is events which have no influence on one another, the rule simplifies to: : ; That is, the probability of the joint events A and B is equal to the product of the individual probabilities for the two events.


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What is probability in risk management?

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If you roll them often enough then the probability is 0. For just one roll, the probability is 35/36.

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What is the describing of the complementary event and find its probability?

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How can you state and illustrate the addition multiplication Theorem of Probability?

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What is the probability of rolling 5 on regular six sided six?

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