User Guide

354
Chapter 19
Range. The difference between the largest and smallest values of a numeric variable;
the maximum minus the minimum.
Skewness. 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 skewness
has a long le
ft tail. As a rough guide, a skewness value more than twice its standard
error is taken to indicate a departure from symmetry.
Standard Error of Kurtosis. The ratio of kurtosis to its standard error can be used as a
test of nor
mality (that is, you can reject normality if the ratio is less than -2 or greater
than +2). A large positive value for kurtosis indicates that the tails of the distribution
are longer than those of a normal distribution; a negative value for kurtosis indicates
shorter t
ails (becoming like those of a box-shaped uniform distribution).
Standard Error of Skewness. The ratio of skewness to its standard error can be used
as a test of normality (that is, you can reject normality if the ratio is less than -2 or
greater t
han +2). A large positive value for skewness indicates a long right tail; an
extreme negative value, a long left tail.
Sum. The sum or total of the values, across all cases with nonmissing values.
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
is measured in units that are the square of those of the variable itself.