Descriptives Options

Mean and Sum. The mean, or arithmetic average, is displayed by default.

Dispersion. Statistics that measure the spread or variation in the data include the standard deviation, variance, range, minimum, maximum, and standard error of the mean.

• Std. deviation. 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 deviation 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 is measured in units that are the square of those of the variable itself.
• Range. The 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. The largest value of a numeric variable.
• 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 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).

Distribution. Kurtosis and skewness are statistics that characterize the shape and symmetry of the distribution. These statistics 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 zero. Positive kurtosis indicates that, relative to a normal distribution, the observations are more clustered about the center of the distribution and have thinner tails until the extreme values of the distribution, at which point the tails of the leptokurtic distribution are thicker relative to a normal distribution. Negative kurtosis indicates that, relative to a normal distribution, the observations cluster less and have thicker tails until the extreme values of the distribution, at which point the tails of the platykurtic distribution are thinner relative to a normal distribution.
• 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.

Display Order. By default, the variables are displayed in the order in which you selected them. Optionally, you can display variables alphabetically, by ascending means, or by descending means.

Specifying Options for Descriptives

1. From the menus choose:

   This feature requires the Statistics Base option.

   Analyze > Descriptive Statistics > Descriptives...

2. In the Descriptives dialog box, click Options.
3. Select one or more statistics.