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Re: [Phys-l] DATA, FACTS, LAWS, THEORIES



On Oct 18, 2009, at 2:40 PM, John Clement wrote:

What follows was prompted by Nicholas Wade's New York Times Book
Review (October 11, 2009). My comment is about scientific DATA, FACTS,
LAWS, THEORIES, ETC. I hope this will be useful. Distinctions between
DATA and FACTS, or between LAWS and THEORIES are important. Comments,
as always, will be appreciated.

c) A LAW is a generalization of facts. I am thinking about Kepler's
Laws (how planets move), about Mendeleyev's Law (how elements are
ordered in a chart), Faraday's Law (how changing currents can be
induced), etc.

d) A THEORY is an explanation of a law. I am thinking about Newton's
gravitational theory, about Maxwell's equations, about quantum
mechanics, about Heizenberg's principle, etc. Distinctions between
laws and theories (and between facts and theories) are worth
recognizing. Unfortunately, this is not always done.

I would assume the article in question is "Evolution All Around" criticizing
the book " THE GREATEST SHOW ON EARTH The Evidence for Evolution"
Richard Dawkins.

1) The review is quite reasonable and actually only differentiates between
theories and facts. It says that Dawkins strays into saying evolution is a
fact and not a theory or model. This looks like a very reasonable criticism
of Dawkins. As far as I can see it makes no general definitions of the
other words.

2) As to a law being a generalization of facts, that is not exactly how the
term is used. Virtually all laws are equations or relationships which may
be either general or specific. If you look at all of the laws they are
generally equations such as Boyle's law, Newton's laws... Sometimes the
equation is merely implied as a statement of a principle.

3) A theory is a consistent framework for relating various laws and facts so
that one can make predictions about unknown situations. Sometimes you
can also call a theory a model. But in no sense is it an explanation. The
theory itself can often not be explained, but it can be used to generate
predictions. If it can be explained that would be in terms of another
theory and eventually you get to postulates or assumptions which have no
explanations, and are sometimes do not even look reasonable, but they work.

4) . . .

I numbered the paragraphs and eliminated the last one; it has nothing to do with the topic of our thread. The above message is a good illustration of disagreements resulting from inprecise terminology. My terminology of the four basic terms (data, facts, laws and explanations) has been introduced.; let me stick to it.

1) Evolution is a theory explaining many facts recognized by biologists. Dawkins, on the other hand, according to the above, states that evolution is a fact. Yes, I know that the term ‘fact’ can refer to different things in common language. That is why scientists must first agree on definitions of basic terms.

2) This paragraph is another illustration of the same thing. I suggest that the term “fact” should refer to validated data (accepted by most practitioners), not to anything else. Likewise, I suggest that the term “law” refers to nothing else than a generalizations of facts.

What is wrong with this approach? How else can we deal with imprecise terminology of common language? As I already mentioned, some people use the words “force,” “energy,” and “power” interchangeably. As physicists we introduced precise definitions of these terms to students, and we try to stick to these definitions. What is wrong with assigning precise meaning to the four concepts needed to discuss scientific validations?

P.S.
Two questions should probably be answered:

a) Do we need precise definitions of basic words used to discuss scientific validations?
b) Are the four concepts i identified (by assigning specific four words to them) indeed essential, as far as scientific validation is concerned?
c) Are the words assigned to these concepts appropriate? If not then what are better words?
Ludwik Kowalski, a retired physics teacher
5 Horizon Road, Apt. 2702, Fort Lee, NJ, 07024, USA
Also an amateur journalist.

Food for thought: "Absence of proof is not proof of absence."

Updated links to his selected publications are at:
http://csam.montclair.edu/~kowalski/cf/ , http://csam.montclair.edu/~kowalski/my_opeds.html and http://csam.montclair.edu/~kowalski/revcom.html