No. Neither the standard deviation nor the variance can ever be negative.
No. The standard deviation is the square root of the variance.
Square the standard deviation and you will have the variance.
is variance the square of the standard deviation
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 = square root of variance.
Standard deviation is the square root of the variance.
The standard deviation is defined as the square root of the variance, so the variance is the same as the squared standard deviation.
Standard deviation, σ = 13.1 Variance, σ2 = 171.6
Variance isn't directly proportional to 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.
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.
Yes, the variance of a data set is the square of the standard deviation (sigma) of the set. This means that the variance is always a positive number, even though the data might have a negative sigma value.