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How do you compute one sigma deviation? - Answers

Let x denote the values of the variable in question. Suppose there are n observations. Let Sx = the sum of all the values. then the mean of x, Mx = Sx/n Let Sxx = the sum of all the squares of the values. The Vx (= the variance of x) is Sxx - (Mx)^2 and sigma(x) = sqrt(Vx). Therefore one sigma deviation, relative to the mean, = Mx - sigma(x), Mx + sigma(x).



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How do you compute one sigma deviation? - Answers

https://math.answers.com/other-math/How_do_you_compute_one_sigma_deviation

Let x denote the values of the variable in question. Suppose there are n observations. Let Sx = the sum of all the values. then the mean of x, Mx = Sx/n Let Sxx = the sum of all the squares of the values. The Vx (= the variance of x) is Sxx - (Mx)^2 and sigma(x) = sqrt(Vx). Therefore one sigma deviation, relative to the mean, = Mx - sigma(x), Mx + sigma(x).



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https://math.answers.com/other-math/How_do_you_compute_one_sigma_deviation

How do you compute one sigma deviation? - Answers

Let x denote the values of the variable in question. Suppose there are n observations. Let Sx = the sum of all the values. then the mean of x, Mx = Sx/n Let Sxx = the sum of all the squares of the values. The Vx (= the variance of x) is Sxx - (Mx)^2 and sigma(x) = sqrt(Vx). Therefore one sigma deviation, relative to the mean, = Mx - sigma(x), Mx + sigma(x).

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      Let x denote the values of the variable in question. Suppose there are n observations. Let Sx = the sum of all the values. then the mean of x, Mx = Sx/n Let Sxx = the sum of all the squares of the values. The Vx (= the variance of x) is Sxx - (Mx)^2 and sigma(x) = sqrt(Vx). Therefore one sigma deviation, relative to the mean, = Mx - sigma(x), Mx + sigma(x).

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