Observability and Learnability as Opposed to ‘Seen and Unseen’

This chapter looks into the nature of observation. Objects of observation are as important as the content and quality of the data. To discern the observable from that of unobservable is the chief task of this chapter. Frédéric Bastiat’s metaphor for ‘Seen and Unseen’ is applied in actual situations. The difference and order of precedence between observability and learnability is also important. The quality of the data is often spoiled with noise. This noise is most of the time unobservable. It created an important problem for statistical inference and thereby scientific inquiry. To understand the content of the data, we need to filter it out of all sources of noise. So Bastiat’s classical metaphor of “seen and unseen” can be extended to an inquiry of noisy data in contemporary business world. The increasing recent researches on this topic will be covered by the chapter.