Display Statistics

The Display Statistics dialog box enables you to choose the statistics displayed on the Audit tab. The initial settings are specified in the Data Audit node. See the topic Data Audit Node Settings Tab for more information.

Minimum. The smallest value of a numeric variable.

Maximum. The largest value of a numeric variable.

Sum. The sum or total of the values, across all cases with nonmissing values.

Range. The difference between the largest and smallest values of a numeric variable, the maximum minus the minimum.

Mean. A measure of central tendency. The arithmetic average, the sum divided by the number of cases.

Standard Error of 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 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 less than -2 or greater than +2).

standard deviation. A measure of dispersion around the mean, equal to the square root of the variance. The standard deviation is measured in the same units as the original variable.

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.

Skewness. A measure of the asymmetry of a distribution. The normal distribution is symmetric and has a skewness value of 0. 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 guideline, a skewness value more than twice its standard error is taken to indicate a departure from symmetry.

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 than +2). A large positive value for skewness indicates a long right tail; an extreme negative value indicates a long left tail.

Kurtosis. A measure of the extent to which there are outliers. For a normal distribution, the value of the kurtosis statistic is zero. Positive kurtosis indicates that the data exhibit more extreme outliers than a normal distribution. Negative kurtosis indicates that the data exhibit less extreme outliers than a normal distribution.

Standard Error of Kurtosis. The ratio of kurtosis 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 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 tails (becoming like those of a box-shaped uniform distribution).

Unique. Evaluates all effects simultaneously, adjusting each effect for all other effects of any type.

Valid. Valid cases having neither the system-missing value, nor a value defined as user-missing. Note that null (undefined) values, blank values, white spaces and empty strings are always treated as invalid values.

Median. The value above and below which half of the cases fall, the 50th percentile. If there is an even number of cases, the median is the average of the two middle cases when they are sorted in ascending or descending order. The median is a measure of central tendency not sensitive to outlying values (unlike the mean, which can be affected by a few extremely high or low values).

Mode. The most frequently occurring value. If several values share the greatest frequency of occurrence, each of them is a mode.

Note that median and mode are suppressed by default in order to improve performance but can be selected on the Settings tab in the Data Audit node. See the topic Data Audit Node Settings Tab for more information.

Statistics for Overlays

If a continuous (numeric range) overlay field is in use, the following statistics are also available:

Covariance. An unstandardized measure of association between two variables, equal to the cross-product deviation divided by N-1.