Introduction

In this chapter, we discuss describing data  sets. Data sets can be thought of as a bunch of numbers or a list of things. For instance, suppose we ask twenty students their weights and then record them as:

122    146     65    162    148    155    136    151    151    153
201    156    235    157    160    171    178    197    142    131

This is a data set of 20 observations. The number of items in a sample is called the sample size  . We often denote the sample size by n . For this data set n = 20.

Next suppose we ask the students their hair color and get the responses:

Red   Blond Blond Brown Brown Red   Blond Blond Brown
Black Blond Red   Red   Brown Black Brown Red   Black
Brown Blond

This is another data set of 20 observations.

Often our data set is a sample   of observations from some reference   . For example, the 20 weights might be sample of the weights of 20 students from a university. We might want to infer   something about the weights of the population based on this sample. These are problems of statistical inference which we will take up in later chapters. In this chapter, though, we just want to discuss ways for describing data sets.

To begin with, basically data come in two types: discrete and continuous .   Discrete data have natural categories while continuous data   do not. The hair color data set is discrete while the weights are continuous. We will treat discrete data first and then continuous data.