This paper attempts to define Exploratory Data Analysis (EDA) more precisely than usual, and to produce the beginnings of a philosophy of this topical and somewhat novel branch of statistics. A data set is, roughly speaking, a collection of k-tuples for some k. In both descriptive statistics and in EDA, these k-tuples, or functions of them, are represented in a manner matched to human and computer abilities with a view to finding patterns that are not "kinkera". A kinkus is a (...) pattern that has a negligible probability of being even partly potentially explicable. A potentially explicable pattern is one for which there probably exists a hypothesis of adequate "explicativity", which is another technical probabilistic concept. A pattern can be judged to be probably potentially explicable even if we cannot find an explanation. The theory of probability understood here is one of partially ordered (interval-valued), subjective (personal) probabilities. Among other topics relevant to a philosophy of EDA are the "reduction" of data; Francis Bacon's philosophy of science; the automatic formulation of hypotheses; successive deepening of hypotheses; neurophysiology; and rationality of type II. (shrink)

The form of argument used by Popper and Miller to attack the concept of probabilistic induction is applied to the slightly different situation in which some evidence undermines a hypothesis. The result is seemingly absurd, thus bringing the form of argument under suspicion.

Review of Mark Wynn's book, Renewing the Senses: A Study of the Philosophy and Theology of the Spiritual Life.

At the start of the 21st century, Corporate Social Responsibility (CSR) seems to have great potential for innovating business practices with a positive impact on People, Planet and Profit. In this article the differences between the management systems approach of the nineties, and Corporate Social Responsibility are analysed.An analysis is structured around three business principles that are relevant for CSR and management systems: (1) doing things right the first time, (2) doing the right things, and (3) continuous improvement and innovation. (...) Basically CSR is focussing on the second principle, and management systems focus on the first. However, CSR is very likely to build on the management systems as well.From a CSR point of view, the existing generation of management systems with their focus on rational control (= doing things right) can only be of limited use in the development of CSR. However, the preventive rationalities of management systems are important. Values and the principle doing the right things is extremely relevant for CSR. This goes far beyond the present generation of ISO type management systems; opportunities stem from building on TQM approaches like the EFQM Business Excellence model. Continuous improvement and innovation is a permanent challenge underlying the two other business principles, and requires both individual and organisational learning processes. In the present generation of management systems, continuous improvement mainly addresses rational prevention, barely the value aspects of business.For the further development and implementation of CSR, each of the three business management principles are vital. There is a need for a new generation of management systems that addresses the values at stake in strategic decision-making, both at company level and in the behaviour of individuals, while the rationalities of prevention and anticipation are still relevant. In both directions more emphasis for continuous learning and innovation will be needed.CSR is likely to trigger the development of management systems in the directions mentioned. This will support companies to be credible and transparent in improving the performance with respect to people, planet and profit. (shrink)

It is shown by means of a simple example that a good explanation of an event is not necessarily corroborated by the occurrence of that event. It is also shown that this contention follows symbolically if an explanation having higher "explicativity" than another is regarded as better.

The use of a concept called "explicativity", for (provisionally) accepting a theory or Hypothesis H, has previously been discussed. That previous discussion took into account the prior probability of H, and hence implicitly its theoretical simplicity. We here suggest that a modification of explicativity is required to allow for what may be called the pragmatic simplicity of H, that is, the simplicity of using H in applications as distinct from the simplicity of the description of H.