Variance is defined as the average of the squared differences from the Mean.
For example, given 600, 470, 170, 430, 300, we have
Mean = (600 + 470 + 170 + 430 + 300) / 5 = 394
The squared differences are as follows:
(600 - 394)2
(470 - 394)2
(179 - 394)2
(430 - 394)2
(300 - 394)2
The average (or mean) of above is 21,704, therefore, the variance is 21,704.
In statistics, Standard Deviation is defined as the square root of Variance. Therefore, in our example above, the Standard Deviation is:
SD = (21,704)1/2 = 147.32...
In statistics, Standard Deviation is a measure used to quantify the amount of variation of a set of data values. A standard deviation close to 0 indicates that the data points tend to be very close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values.