The standard deviation is defined as the square root of the variance, so the variance is the same as the squared standard deviation.
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. Standard deviation is the square root of a non-negative number (the variance) and as such has to be at least zero. Please see the related links for a definition of standard deviation and some examples.
Standard deviation is the square root of the variance. Therefore, the standard deviation is the sqrt 36 or 6.
Square the standard deviation to obtain the variance. The variance is 62 or 36.
Standard deviation is the square root of the variance.
No. The standard deviation is the square root of the variance.
Square the standard deviation and you will have the variance.
Yes. Consider the definition of the standard deviation. It is the square root of the variance from the mean. As a result, it can be said that the standard deviation is dependent on the mean.
Standard deviation = square root of variance.
The standard deviation is defined as the square root of the variance, so the variance is the same as the squared standard deviation.
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, σ = 13.1 Variance, σ2 = 171.6
Variance isn't directly proportional to standard deviation.
No. Neither the standard deviation nor the variance can ever be negative.
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.
Standard deviation is the square root of the variance. Since you stated the variance is 4, the standard deviation is 2.