The central problem of data analysis is the achievement of just the right balance between prior assumptions on the one hand and the findings based on observation of the data on the other hand. This paper is concerned with a special case of this problem. In this paper we are concerned with the empirical fitting of functions of two variables. This problem may be considered as one of surface fitting, or as that of fitting a family of curves. The method is presented in terms of a single example, taken from the recent literature on rubber research. It will be noted that the data are of high precision and it is hoped that this may help to dispel a widespread misconception; namely, the belief that statistical analysis is only useful, or necessary, for data subject to large fluctuations.