The probability of a random variable differing from its mean by more than this value is given by Chebyshev's theorem. This quantity divided by the mean equals the coefficient of variation. Z-values are expressed in units of this value from the mean. This quantity divided by the square root of the sample size equals the standard error. For a normal distribution, around 68% 
The probability of a random variable differing from its mean by more than this value is given by Chebyshev's theorem. This quantity divided by the mean equals the coefficient of variation. Z-values are expressed in units of this value from the mean. This quantity divided by the square root of the sample size equals the standard error. For a normal distribution, around 68% of values lie within this value of the mean. Symbolized by a lowercase sigma, this value is equal to the square root of the variance. For 10 points, name this measure of variation in a distribution.
The probability of a random variable differing from its mean by more than this value is given by Chebyshev's theorem.
standard deviation