18.44 Lecture Notes - Lecture 26: Random Variable, Royal Institute Of Technology, Weighted Arithmetic Mean

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So m(t) is a weighted average of countably many exponential functions. The moment generating function of x is de ned by m(t) = m (t) := e[e ] When x is discrete, can write m(t) = e p (x). When x is continuous, can write m(t) = e f(x) dx. If b > 0 and t > 0 then e[e ] e[e ] p{x b}e. If x takes both positive and negative values with positive probability then m(t) grows at least exponentially fast in |t| as |t| . So m(t) is a weighted average of a continuum of exponential functions. Let x be a random variable and m(t) = e[e ] Then m (t) = / t e[e ] = e[ / t (e )] = e[xe ] Also m (t) = / t m (t) = / t e[xe ] = e[x e ].

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