Data is at the heart of statistical inference. The most basic element of data is a single observation, x, a number. Usually real data comes in the form of a (very long) list of numbers. Even if the original data is more complex — a text, a curve, or an image — we will assume that we can always convert it to a set of n numerical observations x1, . . . , xn, called a sample. To get a better feel for the data in hand, it is often useful (especially if the sample size n is large) to summarize it numerically and graphically. This can bring some insights about the data and help to generate some hypotheses about the data and the underlying phenomenon that produced the data. In this chapter, we will discuss some of the most often used summary statistics.