Difference between revisions of "Draft:Introduction - it"

==Epistemology==

| width="250" align="right" |<small>''The black swan symbolizes one of the historical problems of epistemology: if all the swans we have seen so far are white, can we decide that all the swans are white?<br>Really?''</small>

| width="250" |<small>''Kuhn used optical illusion to demonstrate how a paradigm shift can cause a person to see the same information in a completely different way: which animal is the one here aside?<br>Sure?''</small>

Incidentally, the basic problem of epistemology today, as in Hume’s time, remains that of verifiability.<ref>[[:wikipedia:David Hume|David Hume]] (<!--47-->Edimburgh, 7 <!--48-->may 1711 – <!--49-->Edimburgh, 25 <!--50-->august 1776) <!--51-->was a Scottish philosopher. He is considered the third and perhaps the most radical of the British Empiricists, after the Englishman John Locke and the Anglo-Irish George Berkeley.</ref><ref>{{cita libro  

The Hempel paradox tells us that each sighted white swan confirms that crows are black<ref><!--53-->Here we obviously refer to the well-known paradox called "of the crows", or "of the black crows", formulated by the philosopher and mathematician [[:wikipedia:Carl Gustav Hempel|Carl Gustav Hempel]], <!--54-->better explained in Wikipedia's article ''[https://en.wikipedia.org/w/index.php?title=Raven_paradox&oldid=942633026 Raven paradox]'':<br><!--55-->See {{cita libro

  |anno = 1960|pag=145-149}}</ref>; that is, ''each example not in contrast with the theory confirms a part of it'':<br>

 

According to the objection of falsifiability, instead, no theory is ever true because, while there are only a finite number of experiments in favour, there is also theoretically an infinite number that could falsify it.<ref>{{cita libro  

{{qnq|<!--58-->But it’s not all so obvious...}}

...because the very concept of epistemology meets continuous implementations, like in medicine:

*'''''<math>P-value</math>''''': <br>In medicine, for example, to confirm an experiment, a series of data coming from laboratory instruments or from surveys, the "''Statistical Inference''" is used, and in particular a famous value called "significance test" (P-value). Well, even this concept, now part of the researcher's genesis, is wavering. In a recent study, attention was focused on a "Campaign" conducted on "Nature" against the concept of "significance tests"<ref>{{cita libro  

  }}</ref>.<br />With over 800 signatories supporting important scientists, this "campaign" can be considered an important milestone and a "Silent Revolution" in statistics on logical and epistemological aspects<ref>{{cita libro  

  }}</ref>. The campaign criticizes the too simplified statistical analyses that can still be found in many publications to date.<br>This eventually led to a discussion, sponsored by the American Statistical Association, which spawned a special issue of "The American Statistician Association" titled "''Statistical Inference in the 21st Century: A World Beyond p <0,05''", containing 43 articles by forward-looking statisticians<ref name="wasser">{{cita libro  

  }}</ref>. The special question proposes both new ways to signal the importance of research results beyond the arbitrary threshold of a P-value, and some guides to conduct of research: the researcher should accept uncertainty, be reflective, open and modest in his/ her statements<ref name="wasser" />. Future will show whether or not those attempts to statistically better support science beyond the significance tests will be reflected in future publications<ref>{{cita libro  

  }}</ref>. In this field too, we are on the same wavelength as the Progress of Science according to Kuhn, in that we are talking about the re-modulation of some descriptive statistical contents within the scope of disciplinarity.