Standard deviation is the square root of the variance.
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.
Yes. Please see the related link, below.
The standard error is the standard deviation divided by the square root of the sample size.
The variance is the square of the standard deviation.This question is equivalent tocan s = s^2The answer is yes, but only in two cases.If the standard deviation is 1 exactly, then so is the variance.If the standard deviation is 0 exactly, then so is the variance.If the standard deviation is anything else, then it is not equal to the variance.You are not likely to find these special cases in practical problems, so from a practical sense, you should think that they are generally not equal.
The square of the standard deviation is called the variance. That is because the standard deviation is defined as the square root of the variance.
no it is not possible because you have to take the square of error that is (x-X)2. the square of any number is always positive----------Improved answer:It is not possible to have a negative standard deviation because:SD (standard deviation) is equal to the square of V (variance).
Standard deviation is the square root of the variance.
The standard deviation of a normal deviation is the square root of the mean, also the square root of the variance.
Yes
Standard deviation is equal to the square root of the variance. To arrive at this work out the mean, then subtract the mean and square the result of each number. Then work out the mean of those squared differences and take the square root of that.
Standard deviation = square root of variance.
No. The standard deviation is the square root of the variance.
Square the standard deviation and you will have the variance.
Standard deviation = square root of variance.
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.
Standard deviation is the square root of the variance. Therefore, the standard deviation is the sqrt 36 or 6.