User Guide

311
Frequencies
Dispersion. Statistics that measure the amount of variation or spread in the data
include the standard deviation, variance, range, minimum, maximum, and standard
errorofthe
mean.
 Std. devia
tion.
A measure of dispersion around the mean. In a normal distribution,
68% of cases fall within one standard deviation of the mean and 95% of cases
fall within two standard deviations. For example, if the mean age is 45, with a
standard d
eviation of 10, 95% of the cases would be between 25 and 65 in a
normal distribution.
 Variance. A measure of dispersion around the mean, equal to the sum of squared
deviations from the mean divided by one less than the number of cases. The
variance i
s measured in units that are the square of those of the variable itself.
 Range. Th
e difference between the largest and smallest values of a numeric
variable; the maximum minus the minimum.
 Minimum. The smallest value of a numeric variable.
 Maximum. Thelargestvalueofanumericvariable.
 S. E. mean. A measure of how much the value of the mean may vary from sample
to sample taken from the same distribution. It can be used to roughly compare
the obser
ved mean to a hypothesized value (that is, you can conclude the two
values are different if the ratio of the difference to the standard error is less
than -2 or greater than +2).
Distribution. Skewness and kurtosis are statistics that describe the shape and symmetry
of the dis
tribution. These statistics are displayed with their standard errors.
 Skewnes
s.
A measure of the asymmetry of a distribution. The normal distribution
is symmetric and has a skewness value of zero. A distribution with a significant
positive skewness has a long right tail. A distribution with a significant negative
skewnes
s has a long left tail. As a rough guide, a skewness value more than twice
its standard error is taken to indicate a departure from symmetry.
 Kurtosis. A measure of the extent to which observations cluster around a central
point. For a normal distribution, the value of the kurtosis statistic is 0. Positive
kurtos
is indicates that the observations cluster more and have longer tails than
those in the normal distribution and negative kurtosis indicates the observations
cluster less and have shorter tails.
Values are group midpoints. If the values in your data are midpoints of groups (for
exampl
e, ages of all people in their thirties are coded as 35), select this option to
estimate the median and percentiles for the original, ungrouped data.