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22 Cards in this Set
- Front
- Back
Experiment |
A process that results in some outcome |
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OUTCOME of an experiment
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The results that we observe (sum of 2 dice)
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Sample Space
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The collection of all possible outcomes
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Event
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a collection of 1 or more outcomes from a sample space
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Classical view of Probability
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Based on Theory. Number of favorable outcomes / total number of possible outcomes
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Relative Frequency
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Based on Empirical data. Number of times an event has occurred in the past / the total # of observations
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Subjective Probability
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Based on judgement. What is the possibility that the Phillies will win the World Series?
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Mutually Exclusive
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2 events have no outcomes in common
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0 and 1
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Probability associated with any outcome must be between?
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1
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Sum of all probabilities over all possible outcomes must be?
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The outcomes that compose that event
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Probability of any event is the sum of?
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P(A or B)= P(A)+P(B)
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If events A and B are mutually exclusive then (formula)
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P(A or B)= P(A) + P(B) – P(A and B)
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If events A and B are not mutually exclusive then (formula)
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Conditional Probability
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The probability of the occurrence of one event given that the other event is known to have occurred P(A|B)=P(A and B) / P(B)
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Statistical Independence |
If the probability of A given B = the probability of A; one event conveys no information about the other; P(A|B) = P(A) or P(B|A) = P(B) |
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Probability Density Function
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a curve that characterizes outcomes of a continuous random variable
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Expected Value
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The mean of a random variable |
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Probability Density Function Properties
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(1) f(x)=>0 for all values of x (2)the total area under the function above the x-axis is 1.0 |
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P(A|B) = P(A and B) / P(B) |
Conditional Probability Formula |
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P(A or B) = P(A)+P(B)-P(A and B) |
NOT mutually exclusive formula |
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P(A and B) = P(A) + P(B) |
Mutually Exclusive Formula |
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P(A|B) = P(A) or P(B|A) = P(B) |
Statistical Independence Formula |