User Guide

Chapter
13
Frequencies
The Frequencies procedure provides statistics and graphical displays that are useful
for describing many types of variables. For a first look at your data, the Frequencies
procedure is a good place to start.
For a frequency report and bar chart, you can arrange the distinct values in
ascending or descending order or order the categories by their frequencies. The
frequencies report can be suppressed when a variable has many distinct values. You
can label charts with frequencies (the default) or percentages.
Example. What is the distribution of a company’s customers by industry type? From
the output, you might learn that 37.5% of your customers are in government agencies,
24.9%, in corporations, 28.1%, in academic institutions, and 9.4%, in the healthcare
industry. For continuous, quantitative data, such as sales revenue, you might learn
that the average product sale is $3,576 with a standard deviation of $1,078.
Statistics and plots. Frequency counts, percentages, cumulative percentages, mean,
median, mode, sum, standard deviation, variance, range, minimum and maximum
values, standard error of the mean, skewness and kurtosis (both with standard errors),
quartiles, user-specified percentiles, bar charts, pie charts, and histograms.
Data. Use numeric codes or short strings to code categorical variables (nominal or
ordinal level measurements).
Assumptions. The tabulations and percentages provide a useful description for data
from any distribution, especially for variables with ordered or unordered categories.
Most of the optional summary statistics, such as the mean and standard deviation, are
based on normal theory and are appropriate for quantitative variables with symmetric
distributions. Robust statistics, such as the median, quartiles, and percentiles, are
appropriate for quantitative variables that may or may not meet the assumption of
normality.
307