> and what makes the power of a randome value so special vice just operating on the randome value itself.
Literally four sentences later you would have found:
* The first raw moment E(X) – the mean of the sequence of measurements.
* The second central moment E((X−μX)2) – the variance of the sequence of measurements.
And if you had gotten as far as the part you quoted, you would have seen an extended example of why one is interested in means and variances.
I of course read that next section, and beyond, but respectfully disagree that the expressions provided don't justify further explanation. For example, the author neglects to define 'X' as the set of support values for some probability distribution. That's left to the reader to figure out for some reason. Further, nowhere is 'E(X)' defined as the integral of x*f(x) dx, or that the exponent 'k' only applies to the first 'x' term in that expression (i.e. if k=3, then E(X^3) = integral of (x^3)f(x) dx. How is the reader supposed to know all that?
That was left up to me to hunt down... which is fine I guess, but I certainly wouldn't say this is "from the ground up". At the very least, link to some external content that provides the necessary definitions.
Literally four sentences later you would have found: * The first raw moment E(X) – the mean of the sequence of measurements. * The second central moment E((X−μX)2) – the variance of the sequence of measurements.
And if you had gotten as far as the part you quoted, you would have seen an extended example of why one is interested in means and variances.