Demystifying Science

“Science” is an unnecessarily daunting concept to the uninitiated, which is to say, almost everyone. Because scientific illiteracy is rampant, advocates of policy positions — scientists and non-scientists alike — often are able to invoke “science” wantonly, thus lending unwarranted authority to their positions.


Science is knowledge, but not all knowledge is science. A scientific body of knowledge is systematic; that is, the granular facts or phenomena which comprise the body of knowledge are connected in patterned ways. Moreover, the facts or phenomena represent reality; they are not mere concepts, which may be tools of science but are not science. Beyond that, science — unless it is a purely descriptive body of knowledge — is predictive about the characteristics of as-yet unobserved phenomena. These may be things that exist but have not yet been measured (in terms of the applicable science), or things that are yet to be (as in the effects of new drug on a disease).

Above all, science is not a matter of “consensus” — AGW zealots to the contrary notwithstanding. Science is a matter of rigorously testing theories against facts, and doing it openly. Imagine the state of physics today if Galileo had been unable to question Aristotle’s theory of gravitation, if Newton had been unable to extend and generalize Galileo’s work, and if Einstein had deferred to Newton. The effort to “deny” a prevailing or popular theory is as old as science. There have been “deniers’ in the thousands, each of them responsible for advancing some aspect of knowledge. Not all “deniers” have been as prominent as Einstein (consider Dan Schectman, for example), but each is potentially as important as Einstein.

It is hard for scientists to rise above their human impulses. Einstein, for example, so much wanted quantum physics to be deterministic rather than probabilistic that he said “God does not play dice with the universe.” To which Nils Bohr replied, “Einstein, stop telling God what to do.” But the human urge to be “right” or to be on the “right side” of an issue does not excuse anti-scientific behavior, such as that of so-called scientists who have become invested in AGW.

There are many so-called scientists who subscribe to AGW without having done relevant research. Why? Because AGW is the “in” thing, and they do not wish to be left out. This is the stuff of which “scientific consensus” is made. If you would not buy a make of automobile just because it is endorsed by a celebrity who knows nothing about automotive engineering, why would you “buy” AGW just because it is endorsed by a herd of so-called scientists who have never done research that bears directly on it?

There are two lessons to take from this. The first is  that no theory is ever proven. (A theory may, if it is well and openly tested, be useful guide to action in certain rigorous disciplines, such as engineering and medicine.) Any theory — to be a truly scientific one — must be capable of being tested, even by (and especially by) others who are skeptical of the theory. Those others must be able to verify the facts upon which the theory is predicated, and to replicate the tests and calculations that seem to validate the theory. So-called scientists who restrict access to their data and methods are properly thought of as cultists with a political agenda, not scientists. Their theories are not to be believed — and certainly are not to be taken as guides to action.

The second lesson is that scientists are human and fallible. It is in the best tradition of science to distrust their claims and to dismiss their non-scientific utterances.


Mathematics and statistics are not sciences, despite their vast and organized complexity. They offer ways of thinking about and expressing knowledge, but they are not knowledge. They are languages that enable scientists to converse with each other and outsiders who are fluent in the same languages.

Expressing a theory in mathematical terms may lend the theory a scientific aura. But a theory couched in mathematics (or its verbal equivalent) is not a scientific one unless (a) it can be tested against observable facts by rigorous statistical methods, (b) it is found, consistently, to accord with those facts, and (c) the introduction of new facts does not require adjustment or outright rejection of the theory. If the introduction of new facts requires the adjustment of a theory, then it is a new theory, which must be tested against new facts, and so on.

This “inconvenient fact” — that an adjusted theory is a new theory —  is ignored routinely, especially in the application of regression analysis to a data set for the purpose of quantifying relationships among variables. If a “model” thus derived does a poor job when applied to data outside the original set, it is not an uncommon practice to combine the original and new data and derive a new “model” based on the combined set. This practice (sometimes called data-mining) does not yield scientific theories with predictive power; it yields information (of dubious value) about the the data employed in the regression analysis. As a critic of regression models once put it: Regression is a way of predicting the past with great certainty.

A science may be descriptive rather than mathematical. In a descriptive science (e.g., plant taxonomy), particular phenomena sometimes are described numerically (e.g., the number of leaves on the stem of a species), but the relations among various phenomena are not reducible to mathematics. Nevertheless, a predominantly descriptive discipline will be scientific if the phenomena within its compass are connected in patterned ways.


Non-scientific disciplines can be useful, whereas some purportedly scientific disciplines verge on charlatanism. Thus, for example:

  • History, by my reckoning, is not a science. But a knowledge of history is valuable, nevertheless, for the insights it offers into the influence of human nature on the outcomes of economic and political processes. I call the lessons of history “insights,” not scientific relationships, because history is influenced by so many factors that it does not allow for the rigorous testing of hypotheses.
  • Physics is a science in most of its sub-disciplines, but there are some (e.g., cosmology and certain interpretations of quantum mechanics) where it descends into the realm of speculation. Informed, fascinating speculation to be sure, but speculation all the same. It avoids being pseudo-scientific only because it might give rise to testable hypotheses.
  • Economics is a science only to the extent that it yields valid, statistical insights about specific microeconomic issues (e.g., the effects of laws and regulations on the prices and outputs of goods and services). The postulates of macroeconomics, except to the extent that they are truisms, have no demonstrable validity. (See, for example, my treatment of the Keynesian multiplier.) Macroeconomics is a pseudo-science.


There is no such thing as “science,” writ large; that is, no one may appeal, legitimately, to “science” in the abstract. A particular discipline may be a science, but it is a science only to the extent that it comprises a factual body of knowledge and testable theories. Further, its data and methods must be open to verification and testing. And only a particular theory — one that has been put to the proper tests — can be called a scientific one.

For the reasons adduced in this post, scientists who claim to “know” that there is no God are not practicing science when they make that claim. They are practicing the religion that is known as atheism. The existence or non-existence of God is beyond testing, at least by any means yet known to man.

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