5357016227 | probability | a number between 0 and 1 that describes the proportion of times the outcome would occur in a very long series of repetitions | 0 | |
5357037958 | simulation | A method of modeling chance behavior that accurately mimics the situation being considered. | 1 | |
5357056803 | law of large numbers | in the long run, as the sample size increases, the relative frequencies of outcomes approach the theoretical probability | 2 | |
5831363431 | sample space | The set of all possible outcomes | 3 | |
5831365243 | probability model | description of some chance process that consists of two parts: a sample space S and the probability of each outcome | 4 | |
5831370072 | event | a collection of outcomes from some chance process, a subset of the sample space | 5 | |
5831372392 | mutually exclusive (disjoint) | two events that have no outcomes in common and therefore can never occur together | 6 | |
5831376848 | complement of an event | consists of all possible outcomes in a sample space that are NOT part of the event | 7 | |
5831379134 | Addition Rule for Mutually Exclusive Events | P(A or B) = P(A) + P (B) | 8 | |
5831381638 | General Addition Rule for Two Events | P(A or B) = P(A) + P(B) - P(A and B) | 9 | |
5831387327 | Intersection | P(A and B) | 10 | |
5831387955 | Union | P(A or B) | 11 | |
5831391698 | conditional probability | The probability of an event occurring given that another has occurred. The probability of A given that B has occurred is denoted as P(A|B). | 12 | |
5831393816 | General Multiplication Rule | The probability that events A and B both occur can be found using the formula P(A ∩ B) = P(A) ∙ P(B | A) | 13 | |
5831398305 | tree diagram | Used to display the sample space for a chance process that involves a sequence of outcomes. | 14 | |
5831400220 | independent events | The outcome of one event does not affect the outcome of the second event | 15 | |
5831404726 | Multiplication Rule for Independent events | P(A and B) = P(A) x P(B) | 16 |
AP Stats-Chapter 5 Flashcards
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