| 11. | When the random variable is chi square distribution with degrees of freedom.
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| 12. | The method can also be used on distributional limits of random variables.
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| 13. | The random variable k _ t is characterized by the Binomial distribution
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| 14. | Then this is done again with a new set of random variables.
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| 15. | This is the expected or preferred direction of the angular random variables.
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| 16. | Under this model the references to stored objects are independent random variables.
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| 17. | This may serve as an alternative definition of discrete random variables.
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| 18. | We define that any discrete random variable Y satisfying probability generating function characterization
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| 19. | In its common form, the random variables must be identically distributed.
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| 20. | The maximal information coefficient uses mutual information on continuous random variables.
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