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.
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.
No. Variance and standard deviation are dependent on, but calculated irrespective of the data. You do, of course, have to have some variation, otherwise, the variance and standard deviation will be zero.