Monday, July 11, 2011

Coming to conclusions

In the introduction of E. T. Jaynes's Probability Theory: The Logic of Science, Jaynes states
...the emphasis was therefore on the quantitative formulation of Polya’s viewpoint, so it could be used for general problems of scientific inference, almost all of which arise out of incomplete information rather than ‘randomness’.
As I learn more about the field of sensing, I find that this is the mentality, whether acknowledged by a practitioner or not, that is adopted when coming to a conclusion about the interpretation of data. The uncertainty involved in coming to a conclusion is not because the measurement process is inherently random but rather that one has not collected enough data to say whether this conclusion is true or false.

And in the light of Bayesian analysis, one will never be able to claim with 100% certainty that the conclusion is true (or false, for that matter).