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 = square root of variance.
The SD is the (positive) square root of the 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!
Both variance and standard deviation are measures of dispersion or variability in a set of data. They both measure how far the observations are scattered away from the mean (or average). While computing the variance, you compute the deviation of each observation from the mean, square it and sum all of the squared deviations. This somewhat exaggerates the true picure because the numbers become large when you square them. So, we take the square root of the variance (to compensate for the excess) and this is known as the standard deviation. This is why the standard deviation is more often used than variance but the standard deviation is just the square root of the variance.
The standard deviation or volatility (square root of the variance) of returns.
Standard deviation is the square root of the variance.
Standard deviation = square root of variance.
No. The standard deviation is the square root of the variance.
The SD is the (positive) square root of the variance.
Standard deviation = square root of variance.
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.
Variance is a measure of "relative to the mean, how far away does the other data fall" - it is a measure of dispersion. A high variance would indicate that your data is very much spread out over a large area (random), whereas a low variance would indicate that all your data is very similar.Standard deviation (the square root of the variance) is a measure of "on average, how far away does the data fall from the mean". It can be interpreted in a similar way to the variance, but since it is square rooted, it is less susceptible to outliers.