The addition rule states that given events A and B, the probability of either A or B is given by \(P(\text{A or B}) = P(\text{A}) + P(\text{B}) - P(\text{A and B})\).
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A chance experiment is something that can be done over and over again, and what will happen each time is not known.
For example, each time the spinner is spun, it could land on red, yellow, blue, or green.
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Conditional probability is the likelihood that one event occurs given that another event occurs.
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Events are called dependent when they are from the same experiment and where the outcome of one event affects the probability of another.
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An event is a set of 1 or more outcomes in a chance experiment.
For example, if a number cube is rolled, there are 6 possible outcomes.
Some events are “rolling a number less than 3,” “rolling an even number,” or “rolling a 5.”
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Events are called independent when they are from the same experiment and the outcome of one event does not affect the probability of another.
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An outcome of a chance experiment is one of the things that can happen.
For example, the possible outcomes of tossing a coin are heads and tails.
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The probability of a chance event is a number from 0 to 1 that expresses the likelihood of the event occurring, with 0 meaning it will never occur and 1 meaning it will always occur.
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The sample space is the list of every possible outcome for a chance experiment.
For example, the sample space for tossing two coins is: