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The variance is standard deviation squared, or, in other terms, the standard deviation is the square root of the variance. In many cases, this means that the variance is bigger than the standard deviation - but not always, it depends on the specific values.

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13y ago

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standard deviation has the standard info that the computer can process in its processing chip called the cpu which is technically the brain of the computer but there is more variance because there is a varancial amount of data stored in the computer which means that there is more information than in standard deviation.

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Anonymous

4y ago
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Q: Why variance is bigger than standard deviation?
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Can the Variance ever be smaller than standard deviation?

Yes. If the variance is less than 1, the standard deviation will be greater that the variance. For example, if the variance is 0.5, the standard deviation is sqrt(0.5) or 0.707.


Why standard deviation is more often used than variance?

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.


Can standard deviation value be bigger than maximum and minimum value?

No standard deviation can not be bigger than maximum and minimum values.


Can standard deviation be greater than mean?

Standard deviation can be greater than the mean.


Can the variance be zero?

Variance is standard deviation squared. If standard deviation can be zero then the variance can obviously be zero because zero squared is still zero. The standard deviation is equal to the sum of the squares of each data point in your data set minus the mean, all that over n. The idea is that if all of your data points are the same then the mean will be the same as every data point. If the mean is the equal to every data point then the square of each point minus the mean would be zero. All of the squared values added up would still be zero. And zero divided by n is still zero. In this case the standard deviation would be zero. Short story short: if all of the points in a data set are equal than the variance will be zero. Yes the variance can be zero.