Artikel-Schlagworte: „Reasoning“

The widespread ability to precognize is surely something worth to explore scientifically. If it exists, the researcher who publishes a positive outcome will achieve eternal fame :-). Now, the JPSP will publish a study who tries to validate human’s capability to precognize. A preprint of the experimental study of Bem is available here. 9 experiments were performed with about 1000 participants – quite a huge undertaking! And in 8 of 9 of them it seems that precongition exists. But before you think now that you can also precnogize and go to the next casino and lose your money, let us review how this research was realized. Two articles critizise the original study: One on methodological grounds (Wagenmakers et al) and the other by doing a replication (Galak & Nelson). The replication study failed and Wagenmakers et al. come to the conclusion that the problems of the study of Bem are not related to the fact whether precognition is possible or not but due to the fact that the underlying method was not properly realized. Read for yourself. I think it is worth to mention also that the methodological review uses Bayesian methodology.

Much has been said about induction. I like the following very old citation:

„Yet, in fact, as I shall show here with very good reasons, the properties of the numbers known today have been mostly discovered by observation, and discovered long before their truth has been confirmed by rigid demonstrations. There are even many properties of the numbers with which we are well acquainted, but which we are not yet able to prove; only observations have led us to their knowledge.“

[Euler, Opera Omnia, ser. 1, vol. 2, pp.459, Specimen de usu observationum in mathesi pura]

There were and there are still many arguments about induction and whether induction is possible or not. However, I think this is the wrong question, because it is quite clear that there is nothing which can explain everything. We live in a relative world and if we think we work with mental or mental-somatic models and not with reality itself. Furthermore, anything is part of a context and this leads to the important question of:

  • What from our present context (which elements) has influence on our topic of interest and what has not?
  • How can we describe, understand, explain, forecast, and change these influences?

One of the best short outlines of induction can be found in Jaynes (2003). There, the author also performs a dedicated criticism of Popper’s argument against induction. In short, Jaynes argument that one should work on realistic problems and not just in abstract theory like Popper did. This reveals that one should not compare one theory with every possible imaginable theory, because then no solution at all is possible. This becomes clear at once. Moreover, what is needed is a critical comparison of all available and existent theories. Then, induction makes sense. This process of drawing inferences can be labeled as ‚plausible reasoning‘ which was elaborated by George Polya (1954).

Technically, Bayesian statistics gives much respect to plausible reasoning and consistent argumentation. The Bayes Theorem allows to update the formula in accordance to all known information. In case of new information the formula is updated. By application of the Bayes Theorem it is possible to compare different theoretical approaches and explanations. Then, induction makes sense, because the best of all available theories or hypotheses can be chosen. But ‚best‘ is always ‚relatively best‘ and not an absolute term.

The same can be learned from the teaching of the Buddha: There is relative reality and there is absolute reality (nibbana). However, as long as we live in the realm of relative reality and in the field of sensual experiences of mind and body, it does not make sense to search for anything absolute with is not a product of cause and effect. So we can learn much from Buddhist teaching for scientific purposes.  But we have to remember that the teaching of the Buddha is a practical path of direct experience. It is not an academic and intellectual discussion. It is meant to be applied directly in life. Besides that, we can also mention that the Buddhist teaching involves a very complex system of logic. Some of these ideas actually found their way into psychotherapy and systemic structural sculpturing as it is shown very successfully by Varga von Kibed and Insa Sparrer (2009).


Jaynes, E.T. (2003). Probability Theory. The logic of science (Edited by G.L. Bretthorst). Cambridge University Press.

Polya, G. (1990). Mathematics and plausible reasoning. Volume I: Induction and analogy in mathematics. (First print 1954). Princeton University Press.

Polyga, G. (1990). Mathematics and plausible reasoning. Volume II: Patterns of plausible inference. (First print 1954). Princeton University Press.

Sparrer, I. & Kibed, Varga von (2009). Ganz im Gegenteil: Tetralemmaarbeit und andere Grundformen Systemischer Strukturaufstellungen – für Querdenker und solche, die es werden wollen (6th edition). Heidelberg: Carl-Auer-Systeme.