Hypothetico-deductive model


Hypothetico-deductive model

The hypothetico-deductive model or method, first so-named by William Whewell,[1][2] is a proposed description of scientific method. According to it, scientific inquiry proceeds by formulating a hypothesis in a form that could conceivably be falsified by a test on observable data. A test that could and does run contrary to predictions of the hypothesis is taken as a falsification of the hypothesis. A test that could but does not run contrary to the hypothesis corroborates the theory. It is then proposed to compare the explanatory value of competing hypotheses by testing how stringently they are corroborated by their predictions.

"From the long tradition of empiricism we have inherited the hypothetico-deductive model of scientific research."

—p.86 Brody, Thomas A. (1993), The Philosophy Behind Physics, Springer Verlag, ISBN 0-387-55914-0 . (Luis De La Peña and Peter E. Hodgson, eds.)

Qualification of corroborating evidence is sometimes raised as philosophically problematic. The raven paradox is a famous example. The hypothesis that 'all ravens are black' would appear to be corroborated by observations of only black ravens. However, 'all ravens are black' is logically equivalent to 'all non-black things are non-ravens' (this is the contraposition form of the original implication). 'This is a green tree' is an observation of a non-black thing that is a non-raven and therefore corroborates 'all non-black things are non-ravens'. It appears to follow that the observation 'this is a green tree' is corroborating evidence for the hypothesis 'all ravens are black'. Attempted resolutions may distinguish:

  • non-falsifying observations as to strong, moderate, or weak corroborations
  • investigations that do or do not provide a potentially falsifying test of the hypothesis.[3]

Corroboration is related to the problem of induction, which arises because a general case (a hypothesis) cannot be logically deduced from any series of specific observations. That is, any observation can be seen as corroboration of any hypothesis if the hypothesis is sufficiently restricted. The argument has also been taken as showing that both observations are theory-laden, and thus it is not possible to make truly independent observations. One response is that a problem may be sufficiently narrowed (or axiomatized) as to take everything except the problem (or axiom) of interest as unproblematic for the purpose at hand.[4]

Evidence contrary to a hypothesis is itself philosophically problematic. Such evidence is called a falsification of the hypothesis. However, under the theory of confirmation holism it is always possible to save a given hypothesis from falsification. This is so because any falsifying observation is embedded in a theoretical background, which can be modified in order to save the hypothesis. Popper acknowledged this but maintained that a critical approach respecting methodological rules that avoided such immunizing stratagems is conducive to the progress of science.[5]

Despite the philosophical questions raised, the hypothetico-deductive model remains perhaps the best understood theory of scientific method.

This is an example of an algorithmic statement of the hypothetico-deductive method:[6]

  1. Gather data (observations about something that is unknown, unexplained, or new)
  2. Hypothesize an explanation for those observations.
  3. Deduce a consequence of that explanation (a prediction). Formulate an experiment to see if the predicted consequence is observed.
  4. Wait for corroboration. If there is corroboration, go to step 3. If not, the hypothesis is falsified. Go to step 2.

Notes

  1. ^ William Whewell (1837) History of the Inductive Sciences
  2. ^ William Whewell (1840), Philosophy of the Inductive Sciences
  3. ^ John N.W. Watkins (1984), Science and Skepticism, p. 319.
  4. ^ Karl R. Popper (1963), Conjectures and Refutations, pp. 238-39.
  5. ^ Karl R. Popper (1979, Rev. ed.), Objective Knowledge, pp. 30, 360.
  6. ^ Peter Godfrey-Smith (2003) Theory and Reality, p. 236.

Related subjects

Types of inference


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