In
philosophy of science, strong inference is a
model of scientific inquiry
Models of scientific inquiry have two functions: first, to provide a descriptive account of ''how'' scientific inquiry is carried out in practice, and second, to provide an explanatory account of ''why'' scientific inquiry succeeds as well as it ap ...
that emphasizes the need for
alternative hypotheses, rather than a single hypothesis to avoid
confirmation bias
Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one's prior beliefs or values. People display this bias when they select information that supports their views, ignoring ...
.
The term "strong inference" was coined by
John R. Platt, a
biophysicist at the
University of Chicago. Platt notes that some 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
The problem with single hypotheses,
confirmation bias
Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms or supports one's prior beliefs or values. People display this bias when they select information that supports their views, ignoring ...
, was aptly described by
Thomas Chrowder Chamberlin in 1897:
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
The method, very similar to the scientific method, is described as:
# Devising alternative hypotheses;
# Devising a Experimentum crucis, 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;
# Carrying out the experiment(s) so as to get a clean result;
# Recycling the procedure, making subhypotheses or sequential hypotheses to refine the possibilities that remain, and so on.
Criticisms
The original paper outlining strong inference has been criticized, particularly for overstating the degree that certain fields used this method.
Strong inference plus
The limitations of Strong-Inference can be corrected by having two preceding phases:
# An exploratory phase: at this point information is inadequate so observations are chosen randomly or intuitively or based on
scientific creativity.
# A pilot phase: in this phase
statistical power
In statistics, the power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis (H_0) when a specific alternative hypothesis (H_1) is true. It is commonly denoted by 1-\beta, and represents the chances ...
is determined by replicating experiments under identical experimental conditions.
These phases create the critical seed observation (s) upon which one can base alternative hypotheses.
References
{{DEFAULTSORT:Strong Inference
Scientific method
Inference