Summary Statistics Task

The variables that you assign to this role are the numeric variables for which you want statistics. You must assign at least one variable to this role.

The variables that you assign to this role are character or discrete numeric variables that are used to divide the input data into categories or subgroups. The statistics are calculated on all selected analysis variables for each unique combination of classification variables.

The variables that you assign to this role are used to compute separate statistics for each distinct value or combination of values of the Group analysis by variables. The data is automatically sorted by the variables in this role before the statistics are computed.

When you assign a variable to this role, each observation in the table is assumed to represent n observations, where n is the value of the frequency count for that row. Statistics are calculated accordingly. You can assign a maximum of one variable to this role.

If you assign a variable to this role, the value of the variable for each observation is used to calculate weighted means, variances, and sums. You can assign a maximum of one variable to this role.

is the arithmetic average, calculated by adding the values of an analysis variable and dividing this sum by the number of nonmissing observations.

is a statistical measure of the variability of a group of data values. This measure, which is the most widely used measure of the dispersion of a frequency distribution, is equal to the positive square root of the variance.

is the smallest value for an analysis variable.

is the largest value for an analysis variable.

is the middle value for an analysis variable.

is the total number of observations with nonmissing values.

is the total number of observations with missing values.

is the standard deviation of the sample mean. The standard error is defined as the ratio of the sample standard deviation to the square root of the sample size.

is a statistical measure of dispersion of data values. This measure is an average of the total squared dispersion between each observation and the sample mean.

is the most frequent value for the analysis variable.

is the difference between the largest and smallest values in the data.

is the sum of all values in the analysis variable.

is the sum of the numeric variable that is used to weight each observation.

is the two-sided confidence limits for the mean. A two-sided confidence interval for the mean has the following upper and lower limits: , where s is and is the of the Student’s t statistics with degrees of freedom.

is a unitless measure of relative variability. This measure is defined as the ratio of the standard deviation to the mean expressed as a percentage. The coefficient of variation is meaningful only if the variable is measured on a ratio scale.

is skewness, which measures the tendency of the deviations to be larger in one direction than in the other.

is the kurtosis, which measures the heaviness of tails.

choose the percentiles and quantiles to compute.

creates a graph that is used to determine the distribution of the data. If you add a normal density curve, the task uses the sample mean and sample standard deviation for and . If you add a kernel density curve, the task uses the AMISE method to compute the kernel density estimates.

creates a graph that shows a measure of central location (the median), two measures of dispersion (the range and interquartile range), the skewness (from the orientation of the median relative to the quartiles), and potential outliers. Box plots are especially useful in comparing two or more sets of data.

displays the histogram and box plots together in a single panel, sharing common X axes. You can choose to add the overall inset statistics to the graph.