The information in a random sample is used to make inferences about an unknown parameter theta. If the sample size n is large, then the observed sample is a long list of numbers that is difficult, if not impossible, to interpret. Therefore it is of interest to summarize the information in the sample by determining a few key features of the sample values. This is usually accomplished through computing relevant statistics. Any statistic defines a form of data reduction or data summary. There are three principles of data reduction.  In this lesson, we discuss the sufficiency principle, sufficient statistics, and important theorems and results that aid in finding a sufficient statistic.