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What is 2 standard deviations?

2 times the standard deviation!


How many standard deviations is 19 from the mean?

That depends on what the standard deviation is.


Can the standard deviation or variance be negative?

No, a standard deviation or variance does not have a negative sign. The reason for this is that the deviations from the mean are squared in the formula. Deviations are squared to get rid of signs. In Absolute mean deviation, sum of the deviations is taken ignoring the signs, but there is no justification for doing so. (deviations are not squared here)


How many standard deviations is 99?

You cannot have a standard deviation for 1 number.


Does standard deviation and mean deviation measure dispersion the same?

No. The average of the deviations, or mean deviation, will always be zero. The standard deviation is the average squared deviation which is usually non-zero.


What is the standard deviation for Wechsler intelligence for children?

The mean for the WISC, like the WAIS, is 100. The deviations from 100, or standard deviations, are 15.


How do you find two standard deviations above a mean?

It is mean + 2*standard deviation.


What is the square root of the average of the squared deviations from the mean?

It is the standard deviation.


What is the standard deviation?

The standard deviation of a set of data is a measure of the spread of the observations. It is the square root of the mean squared deviations from the mean of the data.


How do you find highest standard deviation in given number?

Standard deviations are measures of data distributions. Therefore, a single number cannot have meaningful standard deviation.


The mean number is 14 with a standard deviation of 2.5 How many standard deviations is 16.50 from the mean?

16.5 is 1 standard deviation from the mean. If you add the mean of 14 to the 1 standard deviation of 2.5, the result is 16.5.


How is standard deviation useful?

It's used in determining how far from the standard (average) a certain item or data point happen to be. (Ie, one standard deviation; two standard deviations, etc.)