The variance is the square of the standard deviation.
This question is equivalent to
can s = s^2
The 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.
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.
Standard deviation, σ = 13.1 Variance, σ2 = 171.6
Variance isn't directly proportional to standard deviation.
Standard deviation is the square root of the variance. Since you stated the variance is 4, the standard deviation is 2.
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.
It equals 14641.
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.
6.3
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.