Question

the second central moment is always is equal to ?​

Answer 1

Answer:

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If the function is a probability distribution, then the zeroth moment is the total probability (i.e. one), the first moment is the mean, the second central moment is the variance, the third standardized moment is the skewness, and the fourth standardized moment is the kurtosis.

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Answer 2

Answer:

This implies that the second central moment is equivalent to the second raw moment up to a constant. In fact, since E [ X ] 2 \mathbb{E}[X]^2 E[X]2 is nonnegative, we can see that the second moment attains the smallest possible value when taken around the first moment.

Step-by-step explanation:

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