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The Textbook Mentioned That the Mean of Y, E(Y) Y,E(Y2)Y , E \left( Y ^ { 2 } \right)

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The textbook mentioned that the mean of Y, E(Y) is called the first moment of Y , and that the expected value of the square of Y,E(Y2)Y , E \left( Y ^ { 2 } \right) is called the second moment of Y , and so on. These are also referred to as moments about the origin. A related concept is moments about the mean, which are defined as E[(YμY)r]E \left[ \left( Y - \mu _ { Y } \right) ^ { r } \right]
What do you call the second moment about the mean? What do you think the third moment, referred to as "skewness," measures? Do you believe that it would be positive or negative for an earnings distribution? What measure of the third moment around the mean do you get for a normal distribution?

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