The variance is based on the squares of the variable being studied. If, for example, the variable is mass, then the variance is measured in mass-squared. Most people will not be able to wrap their heads around the square of mass. However, the square root will be in the same units of measurement as the variable itself. Thus, the idea of a variable being distributed about a mean, M (also measured in the same units), with a standard deviation (or error) of S is easier to understand.
Second, under reasonable conditions,the transformed variable obtained by subtracting the mean and dividing the result by the standard deviation will have a standard normal distribution. This is extremely important for estimation and hypothesis testing.
Square the standard deviation and you will have the variance.
Standard deviation = square root of variance.
Standard deviation = square root of variance.
If the variance is 846, then the standard deviation is 29.1, the square root of 846.
1. Standard deviation is not a measure of variance: it is the square root of the variance.2. The answer depends on better than WHAT!
Standard deviation is the square root of the variance.
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. 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.
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.
The standard deviation is defined as the square root of the variance, so the variance is the same as the squared standard deviation.
If the variance is 846, then the standard deviation is 29.1, the square root of 846.
Standard deviation is the square root of the variance. Therefore, the standard deviation is the sqrt 36 or 6.
The standard deviation is 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.