Prediction by its derivation (L. praedicere, to say before) means literally the stating beforehand of what will happen at some future time. It is an occupational hazard of many professions: meteorologist, doctor, economist, market researcher, engineering designer, politician and pollster. It is indeed a precarious game because any specific prediction can eventually be compared with the actuality. Many prophets of doom predicting that the world will end at 12.30 on 7 May are left in quieter mood by 12.31. Prediction is a problem simply because of the presence of uncertainty. Seldom, if ever, is it a case of logical deduction; almost inevitably it is a matter of induction or inference. Probabilistic and statistical tools are therefore necessary components of any scientific approach to the formalisation of prediction problems.

In this book we shall be concerned with prediction not only in this narrow sense of making a reasoned statement about what is likely to happen in some future situation but with a much wider class of problems. Any inferential problem whose solution depends on our envisaging some future occurrence will be termed a problem of statistical prediction analysis. The presentation in chapter 1 of a selection of motivating examples illustrates the nature and diversity of statistical prediction analysis, and serves as an introduction to the ingredients of the problem.

A science historian, writing on the development of the concepts and practice of prediction, would probably start by pointing out how primitive man was compelled to attempt prediction, for example the forecasting of the date on which the local river would flood.