Study guides

☆☆

Q: Why do you square the deviation and find the square root of the sum of the square root?

Write your answer...

Submit

Still have questions?

Related questions

No, you have it backwards, the standard deviation is the square root of the variance, so the variance is the standard deviation squared. Usually you find the variance first, as it is the average sum of squares of the distribution, and then find the standard deviation by squaring it.

to find the root-sum square of n numbers you square each number, add them, then take square root of sum For exanple root sum square of 2,3, and 4 is square root of (4+9+16) = sqrt(29) = 5.39

No. It is defined to be the positive square root of ((the sum squared deviation divided by (the number of observations less one))

You can. Just add the numbers together, and find their square root. One plus three is four; the square root of the sum is two.

i think its 5000

The sum of deviations from the mean will always be 0 and so does not provide any useful information. The absolute deviation is one solution to tat, the other is to take the square - and then take a square root.

It's not. Take 49 and 16 for example. The square root of the sum is the square root of 65. The sum of the square roots is 11.

s=sample standard deviation s=square root (Sum(x-(xbar))2 /(n-1) Computing formula (so you don't have to find the mean and the distance from the mean over and over): square root(Sxx /(n-1)) Sxx= Sum(x2) - ((Sum(x))2/n)

standard deviation is the positive square root of mean of the deviations from an arithmatic mean X denoted as sigma.sigma=sqrt {(sum(x-X)^2)/n}

false

Both variance and standard deviation are measures of dispersion or variability in a set of data. They both measure how far the observations are scattered away from the mean (or average). While computing the variance, you compute the deviation of each observation from the mean, square it and sum all of the squared deviations. This somewhat exaggerates the true picure because the numbers become large when you square them. So, we take the square root of the variance (to compensate for the excess) and this is known as the standard deviation. This is why the standard deviation is more often used than variance but the standard deviation is just the square root of the variance.

s is the sample standard deviation. it is computed by taking the square root of: sum(x-mean)2/n-1

People also asked