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If birthdays are uniformly distributed among p = 365 possibilities, for any pair the probability of same birthday is 1/p = 1/365; the expected value (mathematical expectation) of X ij is, by definition, D(X ij ) = 1*(1/p) + 0* 1-1/p) = 1/p.
However small the probability, provided only that it be finite, the mathematical expectation of this wager is infinite.
The mathematical expectation of this game is infinite, but no sensible person would pay a very large sum for the privilege of receiving the payoff from it.
Let μ(f) denote the mathematical expectation of f.
E [ f ] means the mathematical expectation of f.
where μ is the mathematical expectation of x.
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On the other hand, it was shown in 1960 that, although a computable sequence can serve as a set of points in a simple probability space, the mathematical expectations of all random variables X defined on the space can be computed according to an explicit algorithm (see 6) that makes use of the sample values, X a1), X (a2), X a3), · · ·, which themselves are computable if X is computable.
The derivations present that under certain conditions the mathematical expectations of the stochastic tracking errors in the sense of 1-norm converge to zero.
Here, the order of channel fading is (ell=2), the mathematical expectations of the channel coefficients are (bar{alpha}_{0}=0.9, bar {alpha}_{1}=0.4) and (bar{alpha}_{2}= 0.2), and the variances of the channel coefficients are (tilde{alpha}_{0}^=0.25,tilde{alpha}_{1}^=0.64), and (tilde{alpha}_{2}^=0.49).
Mathematical expectations of the amounts and costs of various event types in tubes in this stochastic process are estimated in Stochastic characteristics of the second scenario design.
Changes in residual dispersion patterns could be due to a scale effect when mathematical expectations of two (or more) groups of arrays are different.
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