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19 Cards in this Set
- Front
- Back
Random |
an event in which all outcomes are equally likely |
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Probability |
The chance that something will happen |
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probability model |
A sample space and a way of showing the probabilities of the events |
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sample space |
the set of all possible outcomes |
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event |
any outcome or a set of outcomes of a random phenomenon |
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theoretical probability |
Likelihood that an event will happen |
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Experimental probability |
Observed probability |
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independence |
Two events are independent if knowing that one occurs does not change the probability that the other occurs |
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statistical inference |
drawing conclusions from data that are subject to random variation |
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simulation |
The imitation of chance behavior (based on a model that accurately reflects the phenomenon under consideration) |
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multiplication principal |
If you can do one task n1 number of ways and a second task n2 number of ways, then both tasks can be done in n1 x n2 number of ways |
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disjoint events |
events have no outcomes in common (the probability that one OR the other occurs is the sum of their individual probabilities) |
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complement |
the complement of any event A is the event that A does not occur, written as Ac (the probability that an event does not occur is 1 minus the probability that the event does occur) |
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union |
A union B: the set of all outcomes that are either in A or in B |
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intersection |
A intersect B: the set of all outcomes that are in both A and B |
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empty set |
A set with no outcomes |
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multiplication rule for independent events |
P(A and B) = P(A) x P(B) |
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Can disjoint events be independent (and use the multiplication rule)? |
No |
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If two events are independent, are their complements independent? |
Yes. If two events A and B are independent, then their complements Ac and Bc are also independent, and Ac is independent of B |