Model-free data condensation

Abstract

One aim of data analysis is its condensation, namely capturing its gist in an apposite way. This paper addresses the problem of constructing and assessing such condensations without reference to mechanisms which might have generated the data. The results obtained lead to non-probabilistic interpretations of some well-known inferential procedures of classical statistics and thereby shed new light on the structure of statistical inference and the theory of probability.