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Q: The difference between variance and standard deviation?

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is variance the square of the standard deviation

Standard deviation is the square root of the variance.

The standard deviation is the square root of the variance.

The variance and the standard deviation will decrease.

Standard deviation is the variance from the mean of the data.

Formally, the standard deviation is the square root of the variance. The variance is the mean of the squares of the difference between each observation and their mean value. An easier to remember form for variance is: the mean of the squares minus the square of the mean.

The mean deviation for any distribution is always 0 and so conveys no information whatsoever. The standard deviation is the square root of the variance. The variance of a set of values is the sum of the probability of each value multiplied by the square of its difference from the mean for the set. A simpler way to calculate the variance is Expected value of squares - Square of Expected value.

The mean deviation (also called the mean absolute deviation) is the mean of the absolute deviations of a set of data about the data's mean. The standard deviation sigma of a probability distribution is defined as the square root of the variance sigma^2,

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The variance of a random variable is a measure of its statistical dispersion, indicating how far from the expected value its values typically are (Wikipedia 2006). The variance of a real-valued random variable is its second central moment, and it also happens to be its second cumulant (Wikipedia 2006). The variance of a random variable is the square of its standard deviation (Wikipedia 2006). Variance is the difference between what is expected and the actuals. it is the difference between "should take" and "did take". The deviation from the actuals is called variance. Variance can be of two types positive and negative.

The mean is the average value and the standard deviation is the variation from the mean value.

Standard error is the difference between a researcher's actual findings and their expected findings. Standard error measures the accuracy of one's predictions. Standard deviation is the difference between the results of one's experiment as compared with other results within that experiment. Standard deviation is used to measure the consistency of one's experiment.

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