ABSTRACT
This chapter discusses some basic plots that can provide a useful summary of data. It illustrates basic computations with an eye toward building a foundation for understanding when and why commonly used methods might be unsatisfactory, and why more recently developed methods might have considerable practical value. One of the most common approaches to summarizing a sample of individuals, or a batch of numbers, is to use a so-called measure of location. When considering measures of location, there are two general strategies for dealing with outliers. The first is to trim a specified portion of the largest and smallest values, with the median being the best-known example. The second is to use a measure of location that somehow identifies and eliminates any outliers. The chapter introduces a classic graphical tool for summarizing data called a histogram. Kernel density estimators represent a large class of methods aimed at improving on the histogram.
