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13 Cards in this Set
- Front
- Back
Random Phenomenon
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A phenomenon is random if we know what outcomes could happen, but not which particular values will happen.
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Probability
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The probability of an event is a number between 0 and 1 that reports the likelihood of the event's occurrence. A probability can be derived from equally likely outcomes, from the long-run relative frequency of the event's occurrence, or from known probabilities. We write P(A) for the probability of the event A.
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Trial
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A single attempt or realization of a random phenomenon.
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Outcome
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The outcome of a trial is the value measured, observed, or reported for an individual instance of that trial.
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Event
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A collection of outcomes. Usually, we identify events so that we can attach probabilities to them. We denote these events with bold capital letters such as A, B, or C.
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Independence (informally)
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Two events are independent if knowing whether one event occurs does not alter the probability that the other event occurs.
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Law of Large Numbers
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The Law of Large Numbers states that the long-run relative frequency of repeated independent events settles down to the true relative frequency as the number of trials increases.
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"Something Has to Happen Rule"
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The sum of the probabilities of all possible outcomes must be 1.
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Complement Rule
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The probability of an event occurring is 1 minus the probability that it doesn't occur.
P(A) = 1 - P(Ac) |
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Disjoint (Mutually exclusive)
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Two events are disjoint if they share no outcomes in common. If A and B are disjoint, then knowing that A occurs tells us that B cannot occur. Disjoint events are also called "mutually exclusive."
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Addition Rule
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If A and B are disjoint events, then the probability of A or B is:
P(A or B) = P(A) + P(B). |
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Legitimate probability assignment
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An assignment of probabilities to outcomes is legitimate is
-each probability is between 0 and 1 (inclusive). -the sum of the probabilities is 1. |
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Multiplication Rule
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If A and B are independent events, then the probability of A and B is:
P(A and B) = P(A) X P(B) |