mean and variance of geometric distribution using mgf
As you know multiple different moments of the distribution, you will know more about that distribution. In fact, it need not be defined for any t other than 0. For example, you can completely specify the normal distribution by the first two moments which are a mean and variance. The proof is similar to the proof for the mgf: Distribution function. ELEMENTS OF PROBABILITY DISTRIBUTION THEORY For the exponential distribution we have fX(x) = λe−λxI (0,∞)(x), where λ ∈ R+. The mean is defined as the use of a moment generating function. That is, there is h>0 such that, for all t in h Ethos Menu Wilton Manors,
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