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In philosophy of science, strong inference is a model of scientific inquiry that emphasizes the need for alternative hypotheses, rather than a single hypothesis in order to avoid confirmation bias.

The term "strong inference" was coined by John R. Platt,[1] a biophysicist at the University of Chicago. Platt notes that certain fields, such as molecular biology and high-energy physics, seem to adhere strongly to strong inference, with very beneficial results for the rate of progress in those fields.

The single hypothesis problem[edit | edit source]

The problem with single hypotheses, confirmation bias, was aptly described by Thomas Chrowder Chamberlin in 1897[citation needed]:

The moment one has offered an original explanation for a phenomenon which seems satisfactory, that moment affection for [one’s] intellectual child springs into existence, and as the explanation grows into a definite theory [one’s] parental affections cluster about [the] offspring and it grows more and more dear .... There springs up also unwittingly a pressing of the theory to make it fit the facts and a pressing of the facts to make them fit the theory...

The temptation to misinterpret results that contradict the desired hypothesis is probably irresistible. (Jewett, 2005) [2]

Despite the admonitions of Platt, reviewers of grant-applications often require "A Hypothesis" as part of the proposal (note the singular). Peer-review of research can help avoid the mistakes of single-hypotheses, but only so long as the reviewers are not in the thrall of the same hypothesis. If there is a shared enthrallment among the reviewers in a commonly believed hypothesis, then innovation becomes difficult because alternative hypotheses are not seriously considered, and sometimes not even permitted.

Strong Inference[edit | edit source]

The method, very similar to the scientific method, is described as:

  1. Devising alternative hypotheses;
  2. Devising a crucial experiment (or several of them), with alternative possible outcomes, each of which will, as nearly as possible, exclude one or more of the hypotheses;
  3. Carrying out the experiment so as to get a clean result;
  4. Recycling the procedure, making subhypotheses or sequential hypotheses to refine the possibilities that remain, and so on.

Limitations[edit | edit source]

A number of limitations of strong inference have been identified.[3][4]

Strong inference plus[edit | edit source]

The limitations of Strong-Inference can be corrected by having two preceding phases[2]:

  1. An exploratory phase: at this point information is inadequate so observations are chosen randomly or intuitively or based on scientific creativity.
  2. A pilot phase: in this phase statistical power is determined by replicating experiments under identical experimental conditions.

These phases create the critical seed observation(s) upon which one can base alternative hypotheses.[2]

References[edit | edit source]

  1. John R. Platt (1964). Strong inference. Science 146 (3642).
  2. 2.0 2.1 2.2 Don L. Jewett (1 January 2005). What’s wrong with single hypotheses? Why it is time for Strong-Inference-PLUS. Scientist (Philadelphia, Pa.) 19 (21): 10.
  3. William O'Donohue and Jeffrey A Buchanan (2001). The weaknesses of strong inference. Behavior and Philosophy.
  4. Rowland H. Davis (2006). Strong Inference: rationale or inspiration?. Perspectives in Biology and Medicine 49: 238–250.

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