= 3. The expectation (or average value) of a discrete random variable X is intuitively defined by E(X) = Xxx P[X = x]. Use the concept” about the definition of expectation for discrete case to explain why we define the expectation (or average value) of a continuous random variable, in which its distribution F(x) = P[Y < x] satisfies F'(x)=f(x), to be E(Y) = s y fyd y, -00 if the integral exists. (??? • Please see the next page)

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3. The expectation (or average value) of a discrete random variable X is intuitively
defined by E(X) = Xxx P[X = x]. Use th

= 3. The expectation (or average value) of a discrete random variable X is intuitively defined by E(X) = Xxx P[X = x]. Use the concept” about the definition of expectation for discrete case to explain why we define the expectation (or average value) of a continuous random variable, in which its distribution F(x) = P[Y < x] satisfies F'(x)=f(x), to be E(Y) = s y fyd y, -00 if the integral exists. (??? • Please see the next page)

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