(1)
Mean or Average
The mean or average of a set of values is the sum of the values
divided by the number of the values. Symbolically,
(1)The mean of a number of repeated measurements of an experimental quantity is the best estimate of the true value of the quantity.
Standard deviation
The standard deviation of a set of values is a measure of the typical
distance between the average and any given value. It measures the "width"
of the distribution of values, as shown in the figure.
Imagine plotting a histogram of the horizontal distance x traveled by a projectile launched from a (rather shoddy) spring-loaded launcher. If the projectile is launched a great many times, the distribution of x (in meters) might look like that shown in the figure. The shaded region shows the measurements that are within one standard deviation of the mean. This comprises about 68% of the measured values (68% of the total area under the red curve).
The (sample) standard deviation is defined by
(2)
Standard deviation of the mean (SDOM)
When you perform repeat trials of an experiment to obtain the best possible
estimate of the value of a quantity, as described above, you virtually never obtain the "exact right
answer". Imagine making several launches of the projectile, whose
distribution function is shown in the figure above.
On each measurement, you have about a 68% chance of obtaining a measurement
in the gray region, within one s of the mean. If you make a number of
measurements and average them, though, you will obtain average values that
cluster ever closer to the true mean as you increase the number of
measurements that you average. The distribution of averages narrows around
the true mean, and has a width called the standard deviation of the
mean (SDOM, for short). It is given by
(3)The SDOM is usually the best way to characterize the uncertainty in the average you compute from making n measurements of the same quantity.
Updated 7/6/99 by Peter N. Saeta .