Statistics is commonly taught as a set of techniques to aid in decision making, by extracting information from data. It is argued here that the underlying purpose, often implicit rather than explicit, of every statistical analysis is to establish a set of probability models which can be used to predict values of one or more variables. Such a model constitutes 'information' only in the sense, and to the extent, that it provides predictions of sufficient quality to be useful for decision making. The quality of the decision making is determined by the quality of the predictions, and hence by that of the models used. Using natural criteria, the 'best predictions' for nominal and numeric variables are respectively the mode and mean. For a nominal variable, the quality of a prediction is measured by the probability of error; for a numeric variable, it is specified using a prediction interval. Presenting statistical analysis in this way provides students with a clearer understanding of what a statistical analysis is, and its role in decision making'.