Chapter 3: The UNIVARIATE Procedure

Overview

The UNIVARIATE procedure provides the following:

• descriptive statistics based on moments (including skewness and kurtosis ), quantiles or percentiles (such as the median), frequency tables, and extreme values

• histograms and comparative histograms. Optionally, these can be fitted with probability density curves for various distributions and with kernel density estimates.

• quantile-quantile plots (Q-Q plots) and probability plots. These plots facilitate the comparison of a data distribution with various theoretical distributions.

• goodness-of-fit tests for a variety of distributions including the normal

• the ability to inset summary statistics on plots produced on a graphics device

• the ability to analyze data sets with a frequency variable

• the ability to create output data sets containing summary statistics, histogram intervals, and parameters of fitted curves

You can use the PROC UNIVARIATE statement, together with the VAR statement, to compute summary statistics. See Getting Started on page 196 for introductory examples. In addition, you can use the following statements to request plots:

• the HISTOGRAM statement for creating histograms, the QQPLOT statement for creating Q-Q plots, and the PROBPLOT statement for creating probability plots

• the CLASS statement together with the HISTOGRAM, QQPLOT, and PROBPLOT statement for creating comparative histograms, Q-Q plots, and probability plots

• the INSET statement with any of the plot statements for enhancing the plot with an inset table of summary statistics. The INSET statement is applicable only to plots produced on graphics devices.