Introduction

Engineers continually face the necessity to analyse data and records from the past. These might consist of measurements of material strength, flood records, electronic signals, wave heights in a certain location, or numbers per unit area of icebergs. The intention is to use these records of the past to assess our uncertainty regarding future events. The overall aim is, as always, to make decisions for design at an acceptable level of risk. Apart from good analysis, data provide the most significant means of decreasing uncertainty and improving our probabilistic estimates. Data are obtained from experiments. These always represent an available strategy, although money and effort are required to carry them out. It is the author's experience that in cases where there is considerable uncertainty regarding a physical process, one real experiment is worth a thousand theories.

In the use of probabilistic models two aspects present themselves: the choice of the model itself, and the estimation of model parameters. We showed in Chapter 8 how to use data to estimate parameters of known distributions. The framework described in Section 8.1.1 involved the knowledge of a distribution or process. In the present chapter, we describe the use of data to fit and compare distributions.