User Guide

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Chapter 14

Minimum. The smallest value of a numeric variable.
 Maximum. Thelargestvalueofanumericvariable.
 Standard error of me an. A measure of how much the value of the mean may
vary from sam
ple to sample taken from the same distribution. It can be used to
roughly compare the observed 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 les
s than -2 or greater than +2).
Distributi
on.
Kurtosis and skewness are statistics that characterize the shape and
symmetry of the distribution. These are displayed with their standard errors.
 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
kurtosis indicates that the observations cluster more and have longer tails than
those in the normal distribution and negative kurtosis indicates the observations
cluster le
ss and have shorter tails.
 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 left tail. As a rough guide, a skewness value more than twice
its standard error is taken to indicate a departure from symmetry.
Display Order. By default, the variables are displayed in the order in which you
selecte
d them. Optionally, you can display variables alphabetically, by ascending
means, or by descending means.