| 21. | This random variable has a mean but the variance is infinite.
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| 22. | This makes R _ { app } a random variable too.
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| 23. | This P is a random variable itself and has a distribution.
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| 24. | It also has applications to percolations and probability / random variables.
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| 25. | The joint distribution of binary random variables and can be written
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| 26. | That is as far from independence as random variables can get.
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| 27. | The observed value is just a realization of the random variable.
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| 28. | The Shannon entropy is restricted to random variables taking discrete values.
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| 29. | We say that the discrete random variable Y satisfying probability generating function characterization
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| 30. | Convergence in probability is also called weak convergence of random variables.
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