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18 Cards in this Set
- Front
- Back
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Law of Large Numbers |
As the number of repetitions of a probability experiment increases, the proportion with which a certain outcome is observed gets closer to the probability of the outcome |
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Sample Space (S) |
The collection of all possible outcomes |
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Event |
Any collection of outcomes from a probability experiment. |
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Experiment |
Any process with uncertain results that can be repeated |
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Disjoint Events/Mutually Exclusive Events |
Two events that have no outcomes in common |
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Addition Rule for Disjoint Events |
P(E or F) = P(E) + P(F) |
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Independent Events |
The occurrence of event E in a probability experiment does not affect the probability of event F |
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Multiplication Rule for Independent Events |
P(E and F) = P(E) * P(F) |
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Complement of an Event |
All outcomes in the sample space S that are not outcomes of event E |
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Complement Rule |
P(E^c) = 1 - P(E) |
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General Addition Rule |
P(E or F) = P(E) + P(F) - P(E and F) |
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Conditional Probability |
The probability that the event F occurs, given that the event E has occurred |
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Conditional Probability Rule |
P(F|E) = P(E and F) / P(E) = N(E and F) / N(E) |
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General Multiplication Rule |
P(E and F) = P(E) * P(F|E) |
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Number of Permutations of n Distinct Objects taken r at a Time |
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Number of Combinations of n Distinct Objects taken r at a Time |
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Permutations with Nondistinct Items |
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Bayes's Rule |
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