This chapter presents some general background information on continuous data that is necessary to fully understand the topics on which the book focuses in other chapters (see also Aitken and Taroni 2004; Curran 2011; Lucy 2005). Examinations performed by the application of various analytical methods (Chapter 1) return various kinds of information:
Another way to classify data is connected with the possible values they may generate. If the analysis produces data that can take any value within a specified range, they are considered to be continuous, as opposed to discrete data, which may take certain values. A Typical examples of continuous data are human height and the elemental composition of glass fragments. A typical example of discrete data is the number of children in a family, as it may take only integer values, and cannot take values such as 3.3. Most of the data that chemists have to deal with are of continuous type ...