Scientific method
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The scientific method is an empirical method for acquiring knowledge that has characterized the development of science since at least the 17th century. The scientific method involves careful observation coupled with rigorous scepticism, because cognitive assumptions can distort the interpretation of the observation. Scientific inquiry includes creating a hypothesis through inductive reasoning, testing it through experiments and statistical analysis, and adjusting or discarding the hypothesis based on the results.[1][2][3]
Although procedures vary from one field of inquiry to another, the underlying process is often similar. The process in the scientific method involves making conjectures (hypothetical explanations), deriving predictions from the hypotheses as logical consequences, and then carrying out experiments or empirical observations based on those predictions.[4] A hypothesis is a conjecture based on knowledge obtained while seeking answers to the question. The hypothesis might be very specific or it might be broad. Scientists then test hypotheses by conducting experiments or studies. A scientific hypothesis must be falsifiable, implying that it is possible to identify a possible outcome of an experiment or observation that conflicts with predictions deduced from the hypothesis; otherwise, the hypothesis cannot be meaningfully tested.[5]
While the scientific method is often presented as a fixed sequence of steps, it represents rather a set of general principles.[6] Not all steps take place in every scientific inquiry (nor to the same degree), and they are not always in the same order.[7][8]
History
The history of scientific method considers changes in the methodology of scientific inquiry, as distinct from the history of science itself. The development of rules for scientific reasoning has not been straightforward; scientific method has been the subject of intense and recurring debate throughout the history of science, and eminent natural philosophers and scientists have argued for the primacy of one or another approach to establishing scientific knowledge.
Different early expressions of empiricism and the scientific method can be found throughout history, for instance with the ancient Stoics, Epicurus,[9] Alhazen,[A][a][B] Avicenna, Al-Biruni,[14][15] Roger Bacon[α], and William of Ockham.
In the scientific revolution of the 16th and 17th centuries some of the most important developments were the furthering of empiricism by Francis Bacon and Robert Hooke,[18][19] the rationalist approach described by René Descartes and inductivism, brought to particular prominence by Isaac Newton and those who followed him. Experiments were advocated by Francis Bacon, and performed by Giambattista della Porta,[20] Johannes Kepler,[21][d] and Galileo Galilei.[β] There was particular development aided by theoretical works by a skeptic Francisco Sanches,[23] by idealists as well as empiricists John Locke, George Berkeley, and David Hume.[e]
A sea voyage from America to Europe afforded C. S. Peirce the distance to clarify his ideas, gradually resulting in the hypothetico-deductive model.[26] Formulated in the 20th century, the model has undergone significant revision since first proposed.
The term "scientific method" emerged in the 19th century, as a result of significant institutional development of science, and terminologies establishing clear boundaries between science and non-science, such as "scientist" and "pseudoscience", appearing.[27] Throughout the 1830s and 1850s, when Baconianism was popular, naturalists like William Whewell, John Herschel, John Stuart Mill engaged in debates over "induction" and "facts" and were focused on how to generate knowledge.[27] In the late 19th and early 20th centuries, a debate over realism vs. antirealism was conducted as powerful scientific theories extended beyond the realm of the observable.[28]
Modern use and critical thought
The term "scientific method" came into popular use in the twentieth century; Dewey's 1910 book, How We Think, inspired popular guidelines,[29] appearing in dictionaries and science textbooks, although there was little consensus over its meaning.[27] Although there was growth through the middle of the twentieth century,[f] by the 1960s and 1970s numerous influential philosophers of science such as Thomas Kuhn and Paul Feyerabend had questioned the universality of the "scientific method" and in doing so largely replaced the notion of science as a homogeneous and universal method with that of it being a heterogeneous and local practice.[27] In particular, Paul Feyerabend, in the 1975 first edition of his book Against Method, argued against there being any universal rules of science;[28] Karl Popper,[γ] and Gauch 2003,[6] disagree with Feyerabend's claim.
Later stances include physicist Lee Smolin's 2013 essay "There Is No Scientific Method",[31] in which he espouses two ethical principles,[δ] and historian of science Daniel Thurs' chapter in the 2015 book Newton's Apple and Other Myths about Science, which concluded that the scientific method is a myth or, at best, an idealization.[32] As myths are beliefs,[33] they are subject to the narrative fallacy as Taleb points out.[34] Philosophers Robert Nola and Howard Sankey, in their 2007 book Theories of Scientific Method, said that debates over the scientific method continue, and argued that Feyerabend, despite the title of Against Method, accepted certain rules of method and attempted to justify those rules with a meta methodology.[35] Staddon (2017) argues it is a mistake to try following rules in the absence of an algorithmic scientific method; in that case, "science is best understood through examples".[36][37] But algorithmic methods, such as disproof of existing theory by experiment have been used since Alhacen (1027) Book of Optics,[a] and Galileo (1638) Two New Sciences,[22] and The Assayer[38] still stand as scientific method.
Elements of inquiry
The basic elements of the scientific method are illustrated by the following example (which occurred from 1944 to 1953) from the discovery of the structure of DNA (marked with and indented).
Overview
![](http://upload.wikimedia.org/wikipedia/commons/thumb/8/82/The_Scientific_Method.svg/260px-The_Scientific_Method.svg.png)
There are different ways of outlining the basic method used for scientific inquiry and they are better considered as general principles than a fixed sequence of steps.[7] The scientific community and philosophers of science generally agree on the following classification of method components. These methodological elements and organization of procedures tend to be more characteristic of experimental sciences than social sciences. Nonetheless, the cycle of formulating hypotheses, testing and analyzing the results, and formulating new hypotheses, will resemble the cycle described below. The scientific method is an iterative, cyclical process through which information is continually revised.[39][40] It is generally recognized to develop advances in knowledge through the following elements, in varying combinations or contributions:[41][42]
- Characterizations (observations, definitions, and measurements of the subject of inquiry)
- Hypotheses (theoretical, hypothetical explanations of observations and measurements of the subject)
- Predictions (inductive and deductive reasoning from the hypothesis or theory)
- Experiments (tests of all of the above)
Each element of the scientific method is subject to peer review for possible mistakes. These activities do not describe all that scientists do but apply mostly to experimental sciences (e.g., physics, chemistry, biology, and psychology). The elements above are often taught in the educational system as "the scientific method".[C]
The scientific method is not a single recipe: it requires intelligence, imagination, and creativity.[43] In this sense, it is not a mindless set of standards and procedures to follow but is rather an ongoing cycle, constantly developing more useful, accurate, and comprehensive models and methods. For example, when Einstein developed the Special and General Theories of Relativity, he did not in any way refute or discount Newton's Principia. On the contrary, if the astronomically massive, the feather-light, and the extremely fast are removed from Einstein's theories – all phenomena Newton could not have observed – Newton's equations are what remain. Einstein's theories are expansions and refinements of Newton's theories and, thus, increase confidence in Newton's work.[ε]
An iterative,[40] pragmatic[13] scheme of the four points above is sometimes offered as a guideline for proceeding:[45]
- Define a question
- Gather information and resources (observe)
- Form an explanatory hypothesis
- Test the hypothesis by performing an experiment and collecting data in a reproducible manner
- Analyze the data
- Interpret the data and draw conclusions that serve as a starting point for a new hypothesis
- Publish results
- Retest (frequently done by other scientists)
The iterative cycle inherent in this step-by-step method goes from point 3 to 6 and back to 3 again.
While this schema outlines a typical hypothesis/testing method,[46] many philosophers, historians, and sociologists of science, including Paul Feyerabend,[g] claim that such descriptions of scientific method have little relation to the ways that science is actually practiced.
Characterizations
In 1950, it was known that genetic inheritance had a mathematical description, starting with the studies of Gregor Mendel, and that DNA contained genetic information (Oswald Avery's transforming principle).[48] But the mechanism of storing genetic information (i.e., genes) in DNA was unclear. Researchers in Bragg's laboratory at Cambridge University made X-ray diffraction pictures of various molecules, starting with crystals of salt, and proceeding to more complicated substances. Using clues painstakingly assembled over decades, beginning with its chemical composition, it was determined that it should be possible to characterize the physical structure of DNA, and the X-ray images would be the vehicle.[49]
The scientific method depends upon increasingly sophisticated characterizations of the subjects of investigation. (The subjects can also be called unsolved problems or the unknowns.)[C] For example, Benjamin Franklin conjectured, correctly, that St. Elmo's fire was electrical in nature, but it has taken a long series of experiments and theoretical changes to establish this. While seeking the pertinent properties of the subjects, careful thought may also entail some definitions and observations; these observations often demand careful measurements and/or counting can take the form of expansive empirical research.
A scientific question can refer to the explanation of a specific observation,[C] as in "Why is the sky blue?" but can also be open-ended, as in "How can I design a drug to cure this particular disease?" This stage frequently involves finding and evaluating evidence from previous experiments, personal scientific observations or assertions, as well as the work of other scientists. If the answer is already known, a different question that builds on the evidence can be posed. When applying the scientific method to research, determining a good question can be very difficult and it will affect the outcome of the investigation.[50]
The systematic, careful collection of measurements or counts of relevant quantities is often the critical difference between pseudo-sciences, such as alchemy, and science, such as chemistry or biology. Scientific measurements are usually tabulated, graphed, or mapped, and statistical manipulations, such as correlation and regression, performed on them. The measurements might be made in a controlled setting, such as a laboratory, or made on more or less inaccessible or unmanipulatable objects such as stars or human populations. The measurements often require specialized scientific instruments such as thermometers, spectroscopes, particle accelerators, or voltmeters, and the progress of a scientific field is usually intimately tied to their invention and improvement.
I am not accustomed to saying anything with certainty after only one or two observations.
— Andreas Vesalius, (1546)[51]
Definition
The scientific definition of a term sometimes differs substantially from its natural language usage. For example, mass and weight overlap in meaning in common discourse, but have distinct meanings in mechanics. Scientific quantities are often characterized by their units of measure which can later be described in terms of conventional physical units when communicating the work.
New theories are sometimes developed after realizing certain terms have not previously been sufficiently clearly defined. For example, Albert Einstein's first paper on relativity begins by defining simultaneity and the means for determining length. These ideas were skipped over by Isaac Newton with, "I do not define time, space, place and motion, as being well known to all." Einstein's paper then demonstrates that they (viz., absolute time and length independent of motion) were approximations. Francis Crick cautions us that when characterizing a subject, however, it can be premature to define something when it remains ill-understood.[52] In Crick's study of consciousness, he actually found it easier to study awareness in the visual system, rather than to study free will, for example. His cautionary example was the gene; the gene was much more poorly understood before Watson and Crick's pioneering discovery of the structure of DNA; it would have been counterproductive to spend much time on the definition of the gene, before them.
Hypothesis development
Linus Pauling proposed that DNA might be a triple helix.[53][54] This hypothesis was also considered by Francis Crick and James D. Watson but discarded. When Watson and Crick learned of Pauling's hypothesis, they understood from existing data that Pauling was wrong.[55] and that Pauling would soon admit his difficulties with that structure.
A hypothesis is a suggested explanation of a phenomenon, or alternately a reasoned proposal suggesting a possible correlation between or among a set of phenomena. Normally, hypotheses have the form of a mathematical model. Sometimes, but not always, they can also be formulated as existential statements, stating that some particular instance of the phenomenon being studied has some characteristic and causal explanations, which have the general form of universal statements, stating that every instance of the phenomenon has a particular characteristic.
Scientists are free to use whatever resources they have – their own creativity, ideas from other fields, inductive reasoning, Bayesian inference, and so on – to imagine possible explanations for a phenomenon under study. Albert Einstein once observed that "there is no logical bridge between phenomena and their theoretical principles."[56][h] Charles Sanders Peirce, borrowing a page from Aristotle (Prior Analytics, 2.25)[58] described the incipient stages of inquiry, instigated by the "irritation of doubt" to venture a plausible guess, as abductive reasoning.[59]: II, p.290 The history of science is filled with stories of scientists claiming a "flash of inspiration", or a hunch, which then motivated them to look for evidence to support or refute their idea. Michael Polanyi made such creativity the centerpiece of his discussion of methodology.
William Glen observes that[60]
the success of a hypothesis, or its service to science, lies not simply in its perceived "truth", or power to displace, subsume or reduce a predecessor idea, but perhaps more in its ability to stimulate the research that will illuminate ... bald suppositions and areas of vagueness.
— William Glen, The Mass-Extinction Debates
In general, scientists tend to look for theories that are "elegant" or "beautiful". Scientists often use these terms to refer to a theory that is following the known facts but is nevertheless relatively simple and easy to handle. Occam's Razor serves as a rule of thumb for choosing the most desirable amongst a group of equally explanatory hypotheses.
To minimize the confirmation bias that results from entertaining a single hypothesis, strong inference emphasizes the need for entertaining multiple alternative hypotheses,[61] and avoiding artifacts.[62]
Predictions from the hypothesis
James D. Watson, Francis Crick, and others hypothesized that DNA had a helical structure. This implied that DNA's X-ray diffraction pattern would be 'x shaped'.[63][64] This prediction followed from the work of Cochran, Crick and Vand[65] (and independently by Stokes). The Cochran-Crick-Vand-Stokes theorem provided a mathematical explanation for the empirical observation that diffraction from helical structures produces x-shaped patterns. In their first paper, Watson and Crick also noted that the double helix structure they proposed provided a simple mechanism for DNA replication, writing, "It has not escaped our notice that the specific pairing we have postulated immediately suggests a possible copying mechanism for the genetic material".[66]
Any useful hypothesis will enable predictions, by reasoning including deductive reasoning.[i] It might predict the outcome of an experiment in a laboratory setting or the observation of a phenomenon in nature. The prediction can also be statistical and deal only with probabilities.
It is essential that the outcome of testing such a prediction be currently unknown. Only in this case does a successful outcome increase the probability that the hypothesis is true. If the outcome is already known, it is called a consequence and should have already been considered while formulating the hypothesis.
If the predictions are not accessible by observation or experience, the hypothesis is not yet testable and so will remain to that extent unscientific in a strict sense. A new technology or theory might make the necessary experiments feasible. For example, while a hypothesis on the existence of other intelligent species may be convincing with scientifically based speculation, no known experiment can test this hypothesis. Therefore, science itself can have little to say about the possibility. In the future, a new technique may allow for an experimental test and the speculation would then become part of accepted science.
For example, Einstein's theory of general relativity makes several specific predictions about the observable structure of spacetime, such as that light bends in a gravitational field, and that the amount of bending depends in a precise way on the strength of that gravitational field. Arthur Eddington's observations made during a 1919 solar eclipse supported General Relativity rather than Newtonian gravitation.[67]
Experiments
Watson and Crick showed an initial (and incorrect) proposal for the structure of DNA to a team from King's College London – Rosalind Franklin, Maurice Wilkins, and Raymond Gosling. Franklin immediately spotted the flaws which concerned the water content. Later Watson saw Franklin's photo 51, a detailed X-ray diffraction image, which showed an X-shape[68][69] and was able to confirm the structure was helical.[70][71][j]
Once predictions are made, they can be sought by experiments. If the test results contradict the predictions, the hypotheses which entailed them are called into question and become less tenable. Sometimes the experiments are conducted incorrectly or are not very well designed when compared to a crucial experiment. If the experimental results confirm the predictions, then the hypotheses are considered more likely to be correct, but might still be wrong and continue to be subject to further testing. The experimental control is a technique for dealing with observational error. This technique uses the contrast between multiple samples, or observations, or populations, under differing conditions, to see what varies or what remains the same. We vary the conditions for the acts of measurement, to help isolate what has changed. Mill's canons can then help us figure out what the important factor is.[75] Factor analysis is one technique for discovering the important factor in an effect.
Depending on the predictions, the experiments can have different shapes. It could be a classical experiment in a laboratory setting, a double-blind study or an archaeological excavation. Even taking a plane from New York to Paris is an experiment that tests the aerodynamical hypotheses used for constructing the plane.
These institutions thereby reduce the research function to a cost/benefit,[76] which is expressed as money, and the time and attention of the researchers to be expended,[76] in exchange for a report to their constituents.[77] Current large instruments, such as CERN's Large Hadron Collider (LHC),[78] or LIGO,[79] or the National Ignition Facility (NIF),[80] or the International Space Station (ISS),[81] or the James Webb Space Telescope (JWST),[82][83] entail expected costs of billions of dollars, and timeframes extending over decades. These kinds of institutions affect public policy, on a national or even international basis, and the researchers would require shared access to such machines and their adjunct infrastructure.[ζ][84]
Scientists assume an attitude of openness and accountability on the part of those experimenting. Detailed record-keeping is essential, to aid in recording and reporting on the experimental results, and supports the effectiveness and integrity of the procedure. They will also assist in reproducing the experimental results, likely by others. Traces of this approach can be seen in the work of Hipparchus (190–120 BCE), when determining a value for the precession of the Earth, while controlled experiments can be seen in the works of al-Battani (853–929 CE)[85] and Alhazen (965–1039 CE).[86][k][b]
Communication and iteration
Watson and Crick then produced their model, using this information along with the previously known information about DNA's composition, especially Chargaff's rules of base pairing.[74] After considerable fruitless experimentation, being discouraged by their superior from continuing, and numerous false starts,[88][89][90] Watson and Crick were able to infer the essential structure of DNA by concrete modeling of the physical shapes of the nucleotides which comprise it.[74][91][92] They were guided by the bond lengths which had been deduced by Linus Pauling and by Rosalind Franklin's X-ray diffraction images.
The scientific method is iterative. At any stage, it is possible to refine its accuracy and precision, so that some consideration will lead the scientist to repeat an earlier part of the process. Failure to develop an interesting hypothesis may lead a scientist to re-define the subject under consideration. Failure of a hypothesis to produce interesting and testable predictions may lead to reconsideration of the hypothesis or of the definition of the subject. Failure of an experiment to produce interesting results may lead a scientist to reconsider the experimental method, the hypothesis, or the definition of the subject.
This manner of iteration can span decades and sometimes centuries. Published papers can be built upon. For example: By 1027, Alhazen, based on his measurements of the refraction of light, was able to deduce that outer space was less dense than air, that is: "the body of the heavens is rarer than the body of air".[11] In 1079 Ibn Mu'adh's Treatise On Twilight was able to infer that Earth's atmosphere was 50 miles thick, based on atmospheric refraction of the sun's rays.[l]
This is why the scientific method is often represented as circular – new information leads to new characterisations, and the cycle of science continues. Measurements collected can be archived, passed onwards and used by others. Other scientists may start their own research and enter the process at any stage. They might adopt the characterization and formulate their own hypothesis, or they might adopt the hypothesis and deduce their own predictions. Often the experiment is not done by the person who made the prediction, and the characterization is based on experiments done by someone else. Published results of experiments can also serve as a hypothesis predicting their own reproducibility.
Elements of integrity
Honesty, openness, and falsifiability
The unfettered principles of science are to strive for accuracy and the creed of honesty; openness already being a matter of degrees. Openness is restricted by the general rigour of scepticism. And of course the matter of non-science.
Smolin, in 2013, espoused ethical principles rather than giving any potentially limited definition of the rules of inquiry.[δ] His ideas stand in the context of the scale of data–driven and big science, which has seen increased importance of honesty and consequently reproducibility. His thought is that science is a community effort by those who have accreditation and are working within the community. He also warns against overzealous parsimony.
Popper previously took ethical principles even further, going as far as to ascrible value to theories only if they were falsifiable. Popper used the falsifiability criterion to demarcate a scientific theory from a theory like astrology: both "explain" observations, but the scientific theory takes the risk of making predictions that decide whether it is right or wrong:[94][95]
"Those among us who are unwilling to expose their ideas to the hazard of refutation do not take part in the game of science."
— Karl Popper, The Logic of Scientific Discovery (2002 [1935])
Beliefs and biases
Scientific methodology often directs that hypotheses be tested in controlled conditions wherever possible. This is frequently possible in certain areas, such as in the biological sciences, and more difficult in other areas, such as in astronomy.
The practice of experimental control and reproducibility can have the effect of diminishing the potentially harmful effects of circumstance, and to a degree, personal bias. For example, pre-existing beliefs can alter the interpretation of results, as in confirmation bias; this is a heuristic that leads a person with a particular belief to see things as reinforcing their belief, even if another observer might disagree (in other words, people tend to observe what they expect to observe).[33]
[T]he action of thought is excited by the irritation of doubt, and ceases when belief is attained.
— C.S. Peirce, How to Make Our Ideas Clear (1877)[59]
A historical example is the belief that the legs of a galloping horse are splayed at the point when none of the horse's legs touch the ground, to the point of this image being included in paintings by its supporters. However, the first stop-action pictures of a horse's gallop by Eadweard Muybridge showed this to be false, and that the legs are instead gathered together.[96]
Another important human bias that plays a role is a preference for new, surprising statements (see Appeal to novelty), which can result in a search for evidence that the new is true.[97] Poorly attested beliefs can be believed and acted upon via a less rigorous heuristic.[98]
Goldhaber and Nieto published in 2010 the observation that if theoretical structures with "many closely neighboring subjects are described by connecting theoretical concepts, then the theoretical structure acquires a robustness which makes it increasingly hard – though certainly never impossible – to overturn".[99] When a narrative is constructed its elements become easier to believe.[100][34]
Fleck (1979), p. 27 notes "Words and ideas are originally phonetic and mental equivalences of the experiences coinciding with them. ... Such proto-ideas are at first always too broad and insufficiently specialized. ... Once a structurally complete and closed system of opinions consisting of many details and relations has been formed, it offers enduring resistance to anything that contradicts it". Sometimes, these relations have their elements assumed a priori, or contain some other logical or methodological flaw in the process that ultimately produced them. Donald M. MacKay has analyzed these elements in terms of limits to the accuracy of measurement and has related them to instrumental elements in a category of measurement.[η]
Confirmation
Science is a social enterprise, and scientific work tends to be accepted by the scientific community when it has been confirmed. Crucially, experimental and theoretical results must be reproduced by others within the scientific community. Researchers have given their lives for this vision; Georg Wilhelm Richmann was killed by ball lightning (1753) when attempting to replicate the 1752 kite-flying experiment of Benjamin Franklin.[101]
If an experiment cannot be repeated to produce the same results, this implies that the original results might have been in error. As a result, it is common for a single experiment to be performed multiple times, especially when there are uncontrolled variables or other indications of experimental error. For significant or surprising results, other scientists may also attempt to replicate the results for themselves, especially if those results would be important to their own work.[102] Replication has become a contentious issue in social and biomedical science where treatments are administered to groups of individuals. Typically an experimental group gets the treatment, such as a drug, and the control group gets a placebo. John Ioannidis in 2005 pointed out that the method being used has led to many findings that cannot be replicated.[103]
The process of peer review involves the evaluation of the experiment by experts, who typically give their opinions anonymously. Some journals request that the experimenter provide lists of possible peer reviewers, especially if the field is highly specialized. Peer review does not certify the correctness of the results, only that, in the opinion of the reviewer, the experiments themselves were sound (based on the description supplied by the experimenter). If the work passes peer review, which occasionally may require new experiments requested by the reviewers, it will be published in a peer-reviewed scientific journal. The specific journal that publishes the results indicates the perceived quality of the work.[m]
Scientists typically are careful in recording their data, a requirement promoted by Ludwik Fleck (1896–1961) and others.[104] Though not typically required, they might be requested to supply this data to other scientists who wish to replicate their original results (or parts of their original results), extending to the sharing of any experimental samples that may be difficult to obtain.[105] To protect against bad science and fraudulent data, government research-granting agencies such as the National Science Foundation, and science journals, including Nature and Science, have a policy that researchers must archive their data and methods so that other researchers can test the data and methods and build on the research that has gone before. Scientific data archiving can be done at several national archives in the U.S. or the World Data Center.
Elements of reason
Deductive and inductive reasoning
The idea of there being two opposed justifications for truth has shown up through-out the history of scientific method as analysis versus synthesis, non-ampliative/ampliative, or even confirmation and verification. (And there are other kinds of reasoning.) One to use what is observed to build towards fundamental truths – and the other to derive from those fundamental truths more specific principles.[106]
Deductive reasoning is the building of knowledge based on what has been shown to be true before. It requires the assumption of fact established prior, and, given the truth of the assumptions, a valid deduction guarantees the truth of the conclusion. Inductive reasoning builds knowledge not from established truth, but from a body of observations. It requires stringent scepticism regarding observed phenomena, because cognitive assumptions can distort the interpretation of initial perceptions.[107]
![](http://upload.wikimedia.org/wikipedia/commons/thumb/e/e2/Perihelio.svg/220px-Perihelio.svg.png)
![](http://upload.wikimedia.org/wikipedia/commons/thumb/7/75/Inductive_Deductive_Reasoning.svg/220px-Inductive_Deductive_Reasoning.svg.png)
An example for how inductive and deductive reasoning works can be found in the history of gravitational theory.[n] It took thousands of years of measurements, from the Chaldean, Indian, Persian, Greek, Arabic, and European astronomers, to fully record the motion of planet Earth.[o] Kepler (and others) were then able to build their early theories by generalizing the collected data inductively, and Newton was able to unify prior theory and measurements into the consequences of his laws of motion in 1727.[p]
Another common example of inductive reasoning is the observation of a counterexample to current theory inducing the need for new ideas. Le Verrier in 1859 pointed out problems with the perihelion of Mercury that showed Newton's theory to be at least incomplete. The observed difference of Mercury's precession between Newtonian theory and observation was one of the things that occurred to Einstein as a possible early test of his theory of relativity. His relativistic calculations matched observation much more closely than Newtonian theory did.[q] Though, today's Standard Model of physics suggests that we still do not know at least some of the concepts surrounding Einstein's theory, it holds to this day and is being built on deductively.
A theory being assumed as true and subsequently built on is a common example of deductive reasoning. Theory building on Einstein's achievement can simply state that 'we have shown that this case fulfils the conditions under which general/special relativity applies, therefore its conclusions apply also'. If it was properly shown that 'this case' fulfils the conditions, the conclusion follows. An extension of this is the assumption of a solution to an open problem. This weaker kind of deductive reasoning will get used in current research, when multiple scientists or even teams of researchers are all gradually solving specific cases in working towards proving a larger theory. This often sees hypotheses being revised again and again as new proof emerges.
This way of presenting inductive and deductive reasoning shows part of why science is often presented as being a cycle of iteration. It is important to keep in mind that that cycle's foundations lie in reasoning, and not wholly in the following of procedure.
Hypothetico-deductivism and inductivism
The basics of reasoning along with its interactions with observations and standing theory were introduced above. Specific to hypothesis-testing the HD-method is (non-inductive) standard. "In its simplest form, a sentence of a theory which expresses some hypothesis is confirmed by its true consequences."[112] Basically, scientists will look at the hypothetical consequences a theory holds and prove or disprove those instead of the theory itself. If an experimental test of those hypothetical consequences shows them to be false, it follows logically that the part of the theory that implied them was false also. If they show as true however, it does not prove the theory definitively.
Deductive reasoning based on the assumption of the theory as true leading to further observations is then attributed as a prediction or test and validates the theory. In the example above, if any of the tests of general relativity had returned negative, they would have disproved it. Their positive outcomes, as Hempel put it, provide "at least some support, some corroboration or confirmation for it".[113] The inductive approach should not be dismissed, though. For example in the determination of large primes, where deductive method simply doesn't work.[114]
Confirmation theory
During the course of history, one theory has succeeded another, and some have suggested further work while others have seemed content just to explain the phenomena. The reasons why one theory has replaced another are not always obvious or simple. The philosophy of science includes the question: What criteria are satisfied by a 'good' theory. This question has a long history, and many scientists, as well as philosophers, have considered it. The objective is to be able to choose one theory as preferable to another without introducing cognitive bias.[115] Though different thinkers emphasize different aspects,[ι] a good theory:
- is accurate (the trivial element);
- is consistent, both internally and with other relevant currently accepted theories;
- has explanatory power, meaning its consequences extend beyond the data it is required to explain;
- has unificatory power; as in it's organizing otherwise confused and isolated phenomena
- and is fruitful for further research.
In trying to look for such theories, scientists will, given a lack of guidance by empirical evidence, try to adhere to:
- parsimony in causal explanations
- and look for invariant observations.
- Scientists will sometimes also list the very subjective criteria of "formal elegance" which can indicate multiple different things.
The goal here is to make the choice between theories less arbitrary. Nonetheless, these criteria contain subjective elements, and should be considered heuristics rather than a definitive.[κ] Also, criteria such as these do not necessarily decide between alternative theories. Quoting Bird:[122]
"[Such criteria] cannot determine scientific choice. First, which features of a theory satisfy these criteria may be disputable (e.g. does simplicity concern the ontological commitments of a theory or its mathematical form?). Secondly, these criteria are imprecise, and so there is room for disagreement about the degree to which they hold. Thirdly, there can be disagreement about how they are to be weighted relative to one another, especially when they conflict."
It also is debatable whether existing scientific theories satisfy all these criteria, which may represent goals not yet achieved. For example, explanatory power over all existing observations is satisfied by no one theory at the moment.[123][124]
Parsimony, elegance, and invariance
The desiderata of a "good" theory have been debated for centuries, going back perhaps even earlier than Occam's razor,[r] which is often taken as an attribute of a good theory.
Science tries to be simple. When gathered data supports multiple explanations, the most simple explanation for phenomena or the most simple formation of a theory is recommended by the principle of parsimony.[125] Scientists go as far as to call simple proofs of complex statements beautiful.
We are to admit no more causes of natural things than such as are both true and sufficient to explain their appearances.
— Isaac Newton, Philosophiæ Naturalis Principia Mathematica (1723 [3rd ed.])[1]
Where Newton espoused parsimony in causal explanations, expressed before him in Occam's razor, others after him have expanded on science's general need to be economical.[D] This expanded idea of not just concise theory but the way work is done stands in context with what C. S. Pierce called Musement; inquiry's phase of free-ranging thought.[λ] As he put it: "if we truly desire the goal of the inquiry we are not to waste our resources."[73][4]
Occam's razor might fall under the heading of "simple elegance", but it is arguable that parsimony and elegance pull in different directions. Introducing additional elements could simplify theory formulation, whereas simplifying a theory's ontology might lead to increased syntactical complexity.[121]
Sometimes ad-hoc modifications of a failing idea may also be dismissed as lacking "formal elegance". This appeal to what may be called "aesthetic" is hard to characterise, but essentially about a sort of familiarity. Though, argument based on "elegance" is contentious and over-reliance on familiarity will breed stagnation.[117]
The idea of good ideas being those hard-to-vary has been a theme in scientific writing since at least the early 1900s.[θ] As David Deutsch put it in 2009: "the search for hard-to-vary explanations is the origin of all progress".[119]
Einstein's famous thought experiment of a lab suspended in empty space is an example of a useful invariant observation. He imagined the absence of gravity and an experimenter free floating in the lab. — If now an entity pulls the lab upwards, accelerating uniformly, the experimenter would perceive the resulting force as gravity. The entity however would feel the work needed to accelerate the lab continuously. Through this experiment Einstein was able to equate gravitational and inertial mass; something unexplained by Newton's laws of motion, and an early foundation for his theory of relativity.[s]
The feature, which suggests reality, is always some kind of invariance of a structure independent of the aspect, the projection.
Certainty, probabilities, and statistical inference
Claims of scientific truth can be opposed in three ways: by falsifying them, by questioning their certainty, or by asserting the claim itself to be incoherent.[t] Incoherence, here, means internal errors in logic, like stating opposites to be true; falsification is what Popper would have called the honest work of conjecture and refutation[30] — certainty, perhaps, is where difficulties in telling truths from non-truths arise most easily.
Measurements in scientific work are usually accompanied by estimates of their uncertainty.[76] The uncertainty is often estimated by making repeated measurements of the desired quantity. Uncertainties may also be calculated by consideration of the uncertainties of the individual underlying quantities used. Counts of things, such as the number of people in a nation at a particular time, may also have an uncertainty due to data collection limitations. Or counts may represent a sample of desired quantities, with an uncertainty that depends upon the sampling method used and the number of samples taken.
In the case of measurement imprecision, there will simply be a 'probable deviation' expressing itself in a study's conclusions. Statistics are different. Inductive statistical generalisation will take sample data and extrapolate more general conclusions, which has to be justified — and scrutinised. It can even be said that statistical models are only ever useful, but never a complete representation of circumstances.
In statistical analysis, expected and unexpected bias is a large factor.[127] Research questions, the collection of data, or the interpretation of results, all are subject to larger amounts of scrutiny than in comfortably logical environments. Statistical models go through a process for validation, for which one could even say that awareness of potential biases is more important than the hard logic; errors in logic are easier to find in peer review, after all.[u] More general, claims to rational knowledge, and especially statistics, have to be put into their appropriate context.[107] Simple statements such as '9 out of 10 doctors recommend' are therefore of unknown quality because they do not justify their methodology.
Lack of familiarity with statistical methodologies can result in erroneous conclusions. Foregoing the easy example,[v] multiple probabilities interacting is where, for example medical professionals,[129] have shown a lack of proper understanding. Bayes' theorem is the mathematical principle lining out how standing probabilities are adjusted given new information. The boy or girl paradox is a common example. In knowledge representation, Bayesian estimation of mutual information between random variables is a way to measure dependence, independence, or interdependence of the information under scrutiny.[130]
Beyond commonly associated survey methodology of field research, the concept together with probabilistic reasoning is used to advance fields of science where research objects have no definitive states of being. For example, in statistical mechanics.
Scientific inquiry
Scientific inquiry generally aims to obtain knowledge in the form of testable explanations[131][72] that scientists can use to predict the results of future experiments. This allows scientists to gain a better understanding of the topic under study, and later to use that understanding to intervene in its causal mechanisms (such as to cure disease). The better an explanation is at making predictions, the more useful it frequently can be, and the more likely it will continue to explain a body of evidence better than its alternatives. The most successful explanations – those that explain and make accurate predictions in a wide range of circumstances – are often called scientific theories.[C]
Most experimental results do not produce large changes in human understanding; improvements in theoretical scientific understanding typically result from a gradual process of development over time, sometimes across different domains of science.[132] Scientific models vary in the extent to which they have been experimentally tested and for how long, and in their acceptance in the scientific community. In general, explanations become accepted over time as evidence accumulates on a given topic, and the explanation in question proves more powerful than its alternatives at explaining the evidence. Often subsequent researchers re-formulate the explanations over time, or combined explanations to produce new explanations.
Properties of scientific inquiry
Scientific knowledge is closely tied to empirical findings and can remain subject to falsification if new experimental observations are incompatible with what is found. That is, no theory can ever be considered final since new problematic evidence might be discovered. If such evidence is found, a new theory may be proposed, or (more commonly) it is found that modifications to the previous theory are sufficient to explain the new evidence. The strength of a theory relates to how long it has persisted without major alteration to its core principles.
Theories can also become subsumed by other theories. For example, Newton's laws explained thousands of years of scientific observations of the planets almost perfectly. However, these laws were then determined to be special cases of a more general theory (relativity), which explained both the (previously unexplained) exceptions to Newton's laws and predicted and explained other observations such as the deflection of light by gravity. Thus, in certain cases independent, unconnected, scientific observations can be connected, unified by principles of increasing explanatory power.[133][99]
Since new theories might be more comprehensive than what preceded them, and thus be able to explain more than previous ones, successor theories might be able to meet a higher standard by explaining a larger body of observations than their predecessors.[133] For example, the theory of evolution explains the diversity of life on Earth, how species adapt to their environments, and many other patterns observed in the natural world;[134][135] its most recent major modification was unification with genetics to form the modern evolutionary synthesis. In subsequent modifications, it has also subsumed aspects of many other fields such as biochemistry and molecular biology.
Theory's interactions with observation
It is the nature of science that there is no pure observation as theory is required to interpret empirical data, and observation is influenced by the observer's conceptual framework.[136] The most major discussion on this correlation is the role of prior theory in the testing of new hypotheses.
![](http://upload.wikimedia.org/wikipedia/commons/thumb/5/5a/PositronDiscovery.png/220px-PositronDiscovery.png)
An example here are the experiments of Kepler and Brahe, used by Hanson to illustrate the concept. Despite observing the same sunrise the two scientists came to different conclusions—their intersubjectivity leading to differing conclusions. Johannes Kepler used Tycho Brahe's method of observation, which was to project the image of the Sun on a piece of paper through a pinhole aperture, instead of looking directly at the Sun. He disagreed with Brahe's conclusion that total eclipses of the Sun were impossible because, contrary to Brahe, he knew that there were historical accounts of total eclipses. Instead, he deduced that the images taken would become more accurate, the larger the aperture—this fact is now fundamental for optical system design.[d] Another historic example here is the discovery of Neptune, credited as being found via mathematics because previous observers didn't know what they were looking at.[138]
This is the main argument for the philosophy of scepticism—usually construed as scientific answers being attached to a measure of certainty. Not because science is "wrong" but because science has limits in degrees of being right. Discussions on the topic include the nature of scientific discovery itself, the development of new tools and techniques, and the application of theory to practice; all of which are influenced by the nature of current scientific knowledge.[w]
Empiricism, rationalism, and more pragmatic views
Scientific endeavour can be characterised as the pursuit of truths about the natural world or as the elimination of doubt about the same. The former is the direct construction of explanations from empirical data and logic, the latter the reduction of potential explanations.[μ] It was established above how the interpretation of empirical data is theory-laden, so neither approach is trivial.
The ubiquitous element in the scientific method is empiricism, which holds that knowledge is created by a process involving observation; scientific theories generalize observations. This is in opposition to stringent forms of rationalism, which holds that knowledge is created by the human intellect; later clarified by Popper to be built on prior theory.[140] The scientific method embodies the position that reason alone cannot solve a particular scientific problem; it unequivocally refutes claims that revelation, political or religious dogma, appeals to tradition, commonly held beliefs, common sense, or currently held theories pose the only possible means of demonstrating truth.[13][73]
In 1877,[41] C. S. Peirce characterized inquiry in general not as the pursuit of truth per se but as the struggle to move from irritating, inhibitory doubts born of surprises, disagreements, and the like, and to reach a secure belief, the belief being that on which one is prepared to act. His pragmatic views framed scientific inquiry as part of a broader spectrum and as spurred, like inquiry generally, by actual doubt, not mere verbal or "hyperbolic doubt", which he held to be fruitless.[x] This "hyperbolic doubt" Peirce argues against here is of course just another name for Cartesian doubt associated with René Descartes. It is a methodological route to certain knowledge by identifying what can't be doubted.
A strong formulation of the scientific method is not always aligned with a form of empiricism in which the empirical data is put forward in the form of experience or other abstracted forms of knowledge as in current scientific practice the use of scientific modelling and reliance on abstract typologies and theories is normally accepted. In 2010, Hawking suggested that physics' models of reality should simply be accepted where they prove to make useful predictions. He calls the concept model-dependent realism.[120]
Philosophy
Philosophy of science looks at the underpinning logic of the scientific method, at what separates science from non-science, and the ethic that is implicit in science. There are basic assumptions, derived from philosophy by at least one prominent scientist,[E][143] that form the base of the scientific method – namely, that reality is objective and consistent, that humans have the capacity to perceive reality accurately, and that rational explanations exist for elements of the real world.[143] These assumptions from methodological naturalism form a basis on which science may be grounded. Logical positivist, empiricist, falsificationist, and other theories have criticized these assumptions and given alternative accounts of the logic of science, but each has also itself been criticized.
There are several kinds of modern philosophical conceptualizations and attempts at definitions of the method of science.[ν] The one attempted by the unificationists, who argue for the existence of a unified definition that is useful (or at least 'works' in every context of science). The pluralists, arguing degrees of science being too fractured for a universal definition of its method to by useful. And those, who argue that the very attempt at definition is already detrimental to the free flow of ideas.
Additionally, there have been views on the social framework in which science is done, and the impact of the sciences social envrionment on research. Also, there is 'scientific method' as popularised by Dewey in How We Think (1910) and Karl Pearson in Grammar of Science (1892), as used in fairly uncritical manner in education.
Pluralism
Scientific pluralism is a position within the philosophy of science that rejects various proposed unities of scientific method and subject matter. Scientific pluralists hold that science is not unified in one or more of the following ways: the metaphysics of its subject matter, the epistemology of scientific knowledge, or the research methods and models that should be used. Some pluralists believe that pluralism is necessary due to the nature of science. Others say that since scientific disciplines already vary in practice, there is no reason to believe this variation is wrong until a specific unification is empirically proven. Finally, some hold that pluralism should be allowed for normative reasons, even if unity were possible in theory.
Unificationism
Unificationism, in science, was a central tenet of logical positivism.[145][146] Different logical positivists construed this doctrine in several different ways, e.g. as a reductionist thesis, that the objects investigated by the special sciences reduce to the objects of a common, putatively more basic domain of science, usually thought to be physics; as the thesis that all theories and results of the various sciences can or ought to be expressed in a common language or "universal slang"; or as the thesis that all the special sciences share a common scientific method.[y]
Development of the idea has been troubled by accelerated advancement in technology that has opened up many new ways to look at the world.
The fact that the standards of scientific success shift with time does not only make the philosophy of science difficult; it also raises problems for the public understanding of science. We do not have a fixed scientific method to rally around and defend.
— Steven Weinberg, 1995[144]
Epistemological anarchism
Paul Feyerabend examined the history of science, and was led to deny that science is genuinely a methodological process. In his book Against Method he argued that no description of scientific method could possibly be broad enough to include all the approaches and methods used by scientists, and that there are no useful and exception-free methodological rules governing the progress of science. In essence, he said that for any specific method or norm of science, one can find a historic episode where violating it has contributed to the progress of science. He jokingly suggested that, if believers in the scientific method wish to express a single universally valid rule, it should be 'anything goes'.[148] As has been argued before him however, this is uneconomic; problem solvers, and researchers are to be prudent with their resources during their inquiry.[D]
A more general inference against formalised method has been found through research involving interviews with scientists regarding their conception of method. This research indicated that scientists frequently encounter difficulty in determining whether the available evidence supports their hypotheses. This reveals that there are no straightforward mappings between overarching methodological concepts and precise strategies to direct the conduct of research.[150]
Myth, education, and scientific literacy
In science education, the idea of a general and universal scientific method has been notably influential, and numerous studies (in the US) have shown that this framing of method often forms part of both students’ and teachers’ conception of science.[151][152] This convention of traditional education has been argued against by scientists, as there is a consensus that educations' sequential elements and unified view of scientific method do not reflect how scientists actually work.[153][154][155] Thurs' went as far as to conclude that the scientific method as it is popularised is a myth or, at best, an idealization.[32]
Educations approach to scientific method was inspired by Karl Pearson’s Grammar of Science (1892),[112] and John Dewey's, How We Think (1910).[29][f] Van der Ploeg (2016) indicated that Dewey's views[156] on education had long been used to further an idea of citizen education removed from "sound education", claiming that references to Dewey in such arguments were undue interpretations (of Dewey).[157]
Sociology of knowledge
The sociology of knowledge is a concept in the discussion around scientific method, claiming the underlying method of science to be sociological. King explains that sociology distinguishes here between the system of ideas that govern the sciences through an inner logic, and the social system in which those ideas arise.[ξ]
Thought collectives
A perhaps accessible lead into what is claimed is Fleck's thought, echoed in Kuhn's concept of normal science. According to Fleck, scientists' work is based on a thought-style, that cannot be rationally reconstructed. It gets instilled through the experience of learning, and science is then advanced based on a tradition of shared assumptions held by what he called thought collectives. Fleck also claims this phenomenon to be largely invisible to members of the group.[160]
Comparably, following the field research in an academic scientific laboratory by Latour and Woolgar, Karin Knorr Cetina has conducted a comparative study of two scientific fields (namely high energy physics and molecular biology) to conclude that the epistemic practices and reasonings within both scientific communities are different enough to introduce the concept of "epistemic cultures", in contradiction with the idea that a so-called "scientific method" is unique and a unifying concept.[161][z]
Situated cognition and relativism
On the idea of Fleck's thought collectives sociologists built the concept of situated cognition: that the perspective of the researcher fundamentally affects their work; and, too, more radical views.
Norwood Russell Hanson, alongside Thomas Kuhn and Paul Feyerabend, extensively explored the theory-laden nature of observation in science. Hanson introduced the concept in 1958, emphasizing that observation is influenced by the observer's conceptual framework. He used the concept of gestalt to show how preconceptions can affect both observation and description, and illustrated this with examples like the initial rejection of Golgi bodies as an artefact of staining technique, and the differing interpretations of the same sunrise by Tycho Brahe and Johannes Kepler. Intersubjectivity led to different conclusions.[136][d]
Kuhn and Feyerabend acknowledged Hanson's pioneering work,[165][166] although Feyerabend's views on methodological pluralism were more radical. Criticisms like those from Kuhn and Feyerabend prompted discussions leading to the development of the strong programme, a sociological approach that seeks to explain scientific knowledge without recourse to the truth or validity of scientific theories. It examines how scientific beliefs are shaped by social factors such as power, ideology, and interests.
The postmodernist critiques of science have themselves been the subject of intense controversy. This ongoing debate, known as the science wars, is the result of conflicting values and assumptions between postmodernist and realist perspectives. Postmodernists argue that scientific knowledge is merely a discourse, devoid of any claim to fundamental truth. In contrast, realists within the scientific community maintain that science uncovers real and fundamental truths about reality. Many books have been written by scientists which take on this problem and challenge the assertions of the postmodernists while defending science as a legitimate way of deriving truth.[167]
Limits of method
Role of chance in discovery
![](http://upload.wikimedia.org/wikipedia/commons/thumb/a/a8/Sample_of_penicillin_mould_presented_by_Alexander_Fleming_to_Douglas_Macleod%2C_1935_%289672239344%29.jpg/220px-Sample_of_penicillin_mould_presented_by_Alexander_Fleming_to_Douglas_Macleod%2C_1935_%289672239344%29.jpg)
Somewhere between 33% and 50% of all scientific discoveries are estimated to have been stumbled upon, rather than sought out. This may explain why scientists so often express that they were lucky.[168] Louis Pasteur is credited with the famous saying that "Luck favours the prepared mind", but some psychologists have begun to study what it means to be 'prepared for luck' in the scientific context. Research is showing that scientists are taught various heuristics that tend to harness chance and the unexpected.[168][169] This is what Nassim Nicholas Taleb calls "Anti-fragility"; while some systems of investigation are fragile in the face of human error, human bias, and randomness, the scientific method is more than resistant or tough – it actually benefits from such randomness in many ways (it is anti-fragile). Taleb believes that the more anti-fragile the system, the more it will flourish in the real world.[170]
Psychologist Kevin Dunbar says the process of discovery often starts with researchers finding bugs in their experiments. These unexpected results lead researchers to try to fix what they think is an error in their method. Eventually, the researcher decides the error is too persistent and systematic to be a coincidence. The highly controlled, cautious, and curious aspects of the scientific method are thus what make it well suited for identifying such persistent systematic errors. At this point, the researcher will begin to think of theoretical explanations for the error, often seeking the help of colleagues across different domains of expertise.[168][169]
Relationship with statistics
When the scientific method employs statistics as a key part of its arsenal, there are mathematical and practical issues that can have a deleterious effect on the reliability of the output of scientific methods. This is described in a popular 2005 scientific paper "Why Most Published Research Findings Are False" by John Ioannidis, which is considered foundational to the field of metascience.[128] Much research in metascience seeks to identify poor use of statistics and improve its use, an example being the misuse of p-values.[171]
The particular points raised are statistical ("The smaller the studies conducted in a scientific field, the less likely the research findings are to be true" and "The greater the flexibility in designs, definitions, outcomes, and analytical modes in a scientific field, the less likely the research findings are to be true.") and economical ("The greater the financial and other interests and prejudices in a scientific field, the less likely the research findings are to be true" and "The hotter a scientific field (with more scientific teams involved), the less likely the research findings are to be true.") Hence: "Most research findings are false for most research designs and for most fields" and "As shown, the majority of modern biomedical research is operating in areas with very low pre- and poststudy probability for true findings." However: "Nevertheless, most new discoveries will continue to stem from hypothesis-generating research with low or very low pre-study odds," which means that *new* discoveries will come from research that, when that research started, had low or very low odds (a low or very low chance) of succeeding. Hence, if the scientific method is used to expand the frontiers of knowledge, research into areas that are outside the mainstream will yield the newest discoveries.[needs copy edit]
Science of complex systems
Science applied to complex systems can involve elements such as transdisciplinarity, systems theory, control theory, and scientific modelling.
In general, the scientific method may be difficult to apply stringently to diverse, interconnected systems and large data sets. In particular, practices used within Big data, such as predictive analytics, may be considered to be at odds with the scientific method,[172] as some of the data may have been stripped of the parameters which might be material in alternative hypotheses for an explanation; thus the stripped data would only serve to support the null hypothesis in the predictive analytics application. Fleck (1979), pp. 38–50 notes "a scientific discovery remains incomplete without considerations of the social practices that condition it".[173]
Relationship with mathematics
Science is the process of gathering, comparing, and evaluating proposed models against observables. A model can be a simulation, mathematical or chemical formula, or set of proposed steps. Science is like mathematics in that researchers in both disciplines try to distinguish what is known from what is unknown at each stage of discovery. Models, in both science and mathematics, need to be internally consistent and also ought to be falsifiable (capable of disproof). In mathematics, a statement need not yet be proved; at such a stage, that statement would be called a conjecture.[174]
Mathematical work and scientific work can inspire each other.[38] For example, the technical concept of time arose in science, and timelessness was a hallmark of a mathematical topic. But today, the Poincaré conjecture has been proved using time as a mathematical concept in which objects can flow (see Ricci flow).[175]
Nevertheless, the connection between mathematics and reality (and so science to the extent it describes reality) remains obscure. Eugene Wigner's paper, "The Unreasonable Effectiveness of Mathematics in the Natural Sciences", is a very well-known account of the issue from a Nobel Prize-winning physicist. In fact, some observers (including some well-known mathematicians such as Gregory Chaitin, and others such as Lakoff and Núñez) have suggested that mathematics is the result of practitioner bias and human limitation (including cultural ones), somewhat like the post-modernist view of science.[176]
George Pólya's work on problem solving,[177] the construction of mathematical proofs, and heuristic[178][179] show that the mathematical method and the scientific method differ in detail, while nevertheless resembling each other in using iterative or recursive steps.
In Pólya's view, understanding involves restating unfamiliar definitions in your own words, resorting to geometrical figures, and questioning what we know and do not know already; analysis, which Pólya takes from Pappus,[180] involves free and heuristic construction of plausible arguments, working backward from the goal, and devising a plan for constructing the proof; synthesis is the strict Euclidean exposition of step-by-step details[181] of the proof; review involves reconsidering and re-examining the result and the path taken to it.
Building on Pólya's work, Imre Lakatos argued that mathematicians actually use contradiction, criticism, and revision as principles for improving their work.[182][ο] In like manner to science, where truth is sought, but certainty is not found, in Proofs and Refutations, what Lakatos tried to establish was that no theorem of informal mathematics is final or perfect. This means that, in non-axiomatic mathematics, we should not think that a theorem is ultimately true, only that no counterexample has yet been found. Once a counterexample, i.e. an entity contradicting/not explained by the theorem is found, we adjust the theorem, possibly extending the domain of its validity. This is a continuous way our knowledge accumulates, through the logic and process of proofs and refutations. (However, if axioms are given for a branch of mathematics, this creates a logical system —Wittgenstein 1921 Tractatus Logico-Philosophicus 5.13; Lakatos claimed that proofs from such a system were tautological, i.e. internally logically true, by rewriting forms, as shown by Poincaré, who demonstrated the technique of transforming tautologically true forms (viz. the Euler characteristic) into or out of forms from homology,[183] or more abstractly, from homological algebra.[184][185][ο]
Lakatos proposed an account of mathematical knowledge based on Polya's idea of heuristics. In Proofs and Refutations, Lakatos gave several basic rules for finding proofs and counterexamples to conjectures. He thought that mathematical 'thought experiments' are a valid way to discover mathematical conjectures and proofs.[187]
Gauss, when asked how he came about his theorems, once replied "durch planmässiges Tattonieren" (through systematic palpable experimentation).[188]
See also
- Empirical limits in science – Idea that knowledge comes only/mainly from sensory experience
- Evidence-based practices – Pragmatic methodology
- Methodology – Study of research methods
- Metascience – Scientific study of science
- Quantitative research – All procedures for the numerical representation of empirical facts
- Research transparency
- Scientific law – Statement based on repeated empirical observations that describes some natural phenomenon
- Testability – Extent to which truthness or falseness of a hypothesis/declaration can be tested
- Timeline of the history of scientific method
Notes
- ^ a b Book of Optics (circa 1027) After anatomical investigation of the human eye, and an exhaustive study of human visual perception, Alhacen characterizes the first postulate of Euclid's Optics as 'superfluous and useless' (Book I, [6.54] —thereby overturning Euclid's, Ptolemy's, and Galen's emission theory of vision, using logic and deduction from experiment. He showed Euclid's first postulate of Optics to be hypothetical only, and fails to account for his experiments.), and deduces that light must enter the eye, in order for us to see. He describes the camera obscura as part of this investigation.
- ^ a b Book of Optics Book Seven, Chapter Two [2.1] p.220: — light travels through transparent bodies, such as air, water, glass, transparent stones, in straight lines. "Indeed, this is observable by means of experiment".[87]
- ^ The full title translation is from Voelkel (2001), p. 60.
- ^ a b c Kepler was driven to this experiment after observing the partial solar eclipse at Graz, July 10, 1600. He used Tycho Brahe's method of observation, which was to project the image of the Sun on a piece of paper through a pinhole aperture, instead of looking directly at the Sun. He disagreed with Brahe's conclusion that total eclipses of the Sun were impossible because there were historical accounts of total eclipses. Instead, he deduced that the size of the aperture controls the sharpness of the projected image (the larger the aperture, the more accurate the image – this fact is now fundamental for optical system design). Voelkel (2001), p. 61, notes that Kepler's 1604 experiments produced the first correct account of vision and the eye, because he realized he could not accurately write about astronomical observation by ignoring the eye. Smith (2004), p. 192 recounts how Kepler used Giambattista della Porta's water-filled glass spheres to model the eye, and using an aperture to represent the entrance pupil of the eye, showed that the entire scene at the entrance pupil-focused on a single point of the rear of the glass sphere (representing the retina of the eye). This completed Kepler's investigation of the optical train, as it satisfied his application to astronomy.
- ^ Sanches and Locke were both physicians. By his training in Rome and France, Sanches sought a method of science beyond that of the Scholastic Aristotelian school. Botanical gardens were added to the universities in Sanches' time to aid medical training before the 1600s. See Locke (1689) An Essay Concerning Human Understanding Berkeley served as foil to the materialist System of the World of Newton; Berkeley emphasizes that scientist should seek 'reduction to regularity'.[24] Atherton (ed.) 1999 selects Locke, Berkeley, and Hume as part of the empiricist school.[25]
- ^ a b The struggle to teach science has ranged from recitals of the Neo-platonic First Discourse during the Islamic Golden Age, to Dewey's Laboratory school in 1902. Cowles 2020 notes that Dewey regarded the Lab school as a collaboration between teachers and students. The five-step exposition was taken as mandatory, rather than descriptive. Dismayed by the Procrustean interpretation, Dewey attempted to tone down his five-step scheme by re-naming the steps to phases. The edit was ignored.
- ^ "no opinion, however absurd and incredible, can be imagined, which has not been maintained by some of the philosophers". —Descartes[47]
- ^ "A leap is involved in all thinking" —John Dewey[57]
- ^ From the hypothesis, deduce valid forms using modus ponens, or using modus tollens. Avoid invalid forms such as affirming the consequent.
- ^ The goal shifts: after observing the x-ray diffraction pattern of DNA,[70][69] and as time was of the essence,[72] Watson and Crick realize that fastest way to discover DNA's structure was not by mathematical analysis,[73] but by building physical models.[74]
- ^ Book of Optics Book II [3.52] to [3.66] Summary p.444 for Alhazen's experiments on color; pp.343—394 for his physiological experiments on the eye[86]
- ^ The Sun's rays are still visible at twilight in the morning and evening due to atmospheric refraction even when the depression angle of the sun is 18° below the horizon.[93]
- ^ In Two New Sciences, there are three 'reviewers': Simplicio, Sagredo, and Salviati, who serve as foil, antagonist, and protagonist. Galileo speaks for himself only briefly. But Einstein's 1905 papers were not peer-reviewed before their publication.
- ^ The philosophy of knowledge arising through observation is also called inductivism. A radical proponent of this approach to knowledge was John Stuart Mill who took all knowledge – even mathematical knowledge – to arise from experience through induction. The inductivist approach is still common place, though Mill's extreme views are outdated today.[109]: 35
- ^ Hipparchus used his own observations of the stars, as well as the observations by Chaldean and Babylonian astronomers to estimate Earth's precession.[110]
- ^ Isaac Newton (1727) On the System of the World condensed Kepler's law of for the planetary motion of Mars, Galileo's law of falling bodies, the motion of the planets of the Solar system, etc. into consequences of his three laws of motion.[111] See Motte's translation (1846)
- ^ The difference is approximately 43 arc-seconds per century. And the precession of Mercury's orbit is cited in Tests of general relativity: U. Le Verrier (1859), (in French), "Lettre de M. Le Verrier à M. Faye sur la théorie de Mercure et sur le mouvement du périhélie de cette planète", Comptes rendus hebdomadaires des séances de l'Académie des sciences (Paris), vol. 49 (1859), pp.379–383.
- ^ Occam's razor, sometimes referred to as "ontological parsimony", is roughly stated as: Given a choice between two theories, the simplest is the best. This suggestion commonly is attributed to William of Ockham in the 14th-century, although it probably predates him.[121]
- ^ Arthur Eddington, 1920: "The relativity theory of physics reduces everything to relations; that is to say, it is structure, not material, which counts." — Weinert, giving the Einstein example and quoting: "Eddington, Space, Time and Gravitation (1920), 197"[118]
- ^ ...simplified and (post-modern) philosophy notwithstanding.[126]
- ^ ... and John Ioannidis, in 2005,[128] has shown that not everybody respects the principles of statistical analysis; whether they be the principles of inference or otherwise.
- ^ For instance, extrapolating from a single scientific observation, such as "This experiment yielded these results, so it should apply broadly," exemplifies inductive wishful thinking. Statistical generalisation is a form of inductive reasoning. Conversely, assuming that a specific outcome will occur based on general trends observed across multiple experiments, as in "Most experiments have shown this pattern, so it will likely occur in this case as well," illustrates faulty deductive probability logic.
- ^ ...the exception to every rational argument of course being discovery by chance.
- ^ "What one does not in the least doubt one should not pretend to doubt; but a man should train himself to doubt," said Peirce in a brief intellectual autobiography.[141] Peirce held that actual, genuine doubt originates externally, usually in surprise, but also that it is to be sought and cultivated, "provided only that it be the weighty and noble metal itself, and no counterfeit nor paper substitute".[142]
- ^ The topics of study, as expressed in the vocabulary of its scientists, are approached by a "single unified method".[29]: pp.8, 13, 33–35, 60 A topic is unified by its predicates, which describe a system of mathematical expressions.[147]: 93–94, 113–117 The values which a predicate might take, then serve as witness to the validity of a predicated expression (that is, true or false; 'predicted but not yet observed'; 'corroborates', etc.).
- ^ Comparing 'epistemic cultures' with Fleck 1935, Thought collectives, (denkkollektiven): Entstehung und Entwicklung einer wissenschaftlichen Tatsache: Einfǖhrung in die Lehre vom Denkstil und Denkkollektiv[162] Fleck (1979), p. xxvii recognizes that facts have lifetimes, flourishing only after incubation periods. His selected question for investigation (1934) was "HOW, THEN, DID THIS EMPIRICAL FACT ORIGINATE AND IN WHAT DOES IT CONSIST?".[163] But by Fleck 1979, p.27, the thought collectives within the respective fields will have to settle on common specialized terminology, publish their results and further intercommunicate with their colleagues using the common terminology, in order to progress.[164]
Notes: Problem-solving via scientific method
- ^ Twenty-three hundred years ago, Aristotle proposed that a vacuum did not exist in nature; thirteen hundred years later, Alhazen disproved Aristotle's hypothesis, using experiments on refraction,[10] thus deducing the existence of outer space.[11]
- ^ Alhazen argued the importance of forming questions and subsequently testing them: "How does light travel through transparent bodies? Light travels through transparent bodies in straight lines only... We have explained this exhaustively in our Book of Optics.[b] But let us now mention something to prove this convincingly: the fact that light travels in straight lines is clearly observed in the lights which enter into dark rooms through holes.... [T]he entering light will be clearly observable in the dust which fills the air.[12]
- He demonstrated his conjecture that "light travels through transparent bodies in straight lines only" by placing a straight stick or a taut thread next to the light beam, as quoted in Sambursky (1975), p. 136 to prove that light travels in a straight line.
- David Hockney cites Alhazen several times as the likely source for the portraiture technique using the camera obscura, which Hockney rediscovered with the aid of an optical suggestion from Charles M. Falco. Kitab al-Manazir, which is Alhazen's Book of Optics, at that time denoted Opticae Thesaurus, Alhazen Arabis, was translated from Arabic into Latin for European use as early as 1270. Hockney cites Friedrich Risner's 1572 Basle edition of Opticae Thesaurus. Hockney quotes Alhazen as the first clear description of the camera obscura.[13]
- ^ a b c d In the inquiry-based education paradigm, the stage of "characterization, observation, definition, ..." is more briefly summed up under the rubric of a Question. The question at some stage might be as basic as the 5Ws, or is this answer true?, or who else might know this?, or can I ask them?, and so forth. The questions of the inquirer spiral until the goal is reached.
- ^ a b Peirce (1899) First rule of logic (F.R.L)[73] Paragraph 1.136: From the first rule of logic, if we truly desire the goal of the inquiry we are not to waste our resources.[72][131] — Terence Tao wrote on the matter that not all approaches can be regarded as "equally suitable and deserving of equal resources" because such positions would "sap mathematics of its sense of direction and purpose".[149]
- ^ Never fail to recognize an idea... .— C. S. Peirce, ILLUSTRATIONS OF THE LOGIC OF SCIENCE, SECOND PAPER. —HOW TO MAKE OUR IDEAS CLEAR. Popular Science Monthly Volume 12, January 1878, p.286[59]
Notes: Philosophical expressions of method
- ^ His assertions in the Opus Majus that "theories supplied by reason should be verified by sensory data, aided by instruments, and corroborated by trustworthy witnesses"[16] were (and still are) considered "one of the first important formulations of the scientific method on record".[17]
- ^ ...an experimental approach was advocated by Galileo in 1638 with the publication of Two New Sciences.[22]
- ^ Popper, in his 1963 publication of Conjectures and Refutations argued that merely Trial and Error can stand to be called a 'universal method'.[30]
- ^ a b Lee Smolin, in his 2013 essay "There Is No Scientific Method",[31] espouses two ethical principles. Firstly: "we agree to tell the truth and we agree to be governed by rational argument from public evidence". And secondly, that ..."when the evidence is not sufficient to decide from rational argument, whether one point of view is right or another point of view is right, we agree to encourage competition and diversification". Thus echoing Popper (1963), p. viii
- ^ When asked how he arrived at his law of universal gravitation, Newton replied "By thinking on it continually." —Westfall 1983.[44]
- ^ The machinery of the mind can only transform knowledge, but never originate it, unless it be fed with facts of observation. —C.S. Peirce[59]
- ^ The scientific method requires testing and validation a posteriori before ideas are accepted.[76]
- ^ a b Friedel Weinert in The Scientist as Philosopher (2004) noted the theme of invariance as a fundamental aspect of a scientific account of reality in many writings from around 1900 onward, such as works by Henri Poincaré (1902), Ernst Cassirer (1920), Max Born (1949 and 1953), Paul Dirac (1958), Olivier Costa de Beauregard (1966), Eugene Wigner (1967), Lawrence Sklar (1974), Michael Friedman (1983), John D. Norton (1992), Nicholas Maxwell (1993), Alan Cook (1994), Alistair Cameron Crombie (1994), Margaret Morrison (1995), Richard Feynman (1997), Robert Nozick (2001), and Tim Maudlin (2002).[118] — Deutsch in a 2009 TED talk proclaimed that "the search for hard-to-vary explanations is the origin of all progress".[119]
- ^ Differing accounts of which elements constitute a good theory:
- Kuhn (1977) identified: accuracy; consistency (both internal and with other relevant currently accepted theories); scope (its consequences should extend beyond the data it is required to explain); simplicity (organizing otherwise confused and isolated phenomena); fruitfulness (for further research);[116]
- Colyvan (2001) listed simplicity/parsimony, unificatory/explanatory power, boldness/fruitfulness, and elegance;[117]
- Weinert (2004) noted the recurring theme of invariance;[θ]
- Hawking (2010): simplicity/parsimony, unificatory/explanatory power, and elegance, but did not mention fruitfulness.[120]
- ^ ...Hawking & Mlodinow on criteria for a good theory: "The above criteria are obviously subjective. Elegance, for example, is not something easily measured, but it is highly prized among scientists." The idea of 'too baroque' is connected to 'simplicity': "a theory jammed with fudge factors is not very elegant. To paraphrase Einstein, a theory should be as simple as possible, but not simpler".[120] See also:[121]
- ^ C. S. Pierce called inquiry's phase of free-ranging thought Musement. It carried attendant feelings of doubt, belief, perplexity etc. According to him, this phase of inquiry with no attempt at discovery of an order stands in order prior to retrodiction (the evaluation of what is known) and abduction.[4]
- ^ "At the heart of science is an essential balance between two seemingly contradictory attitudes—an openness to new ideas, no matter how bizarre or counterintuitive, and the most ruthlessly skeptical scrutiny of all ideas, old and new. This is how deep truths are winnowed from deep nonsense." — Carl Sagan[139]
- ^ There is no universally agreed upon definition of the method of science. This was expressed with Neurath's boat already in 1913. There is however a consensus that stating this somewhat nihilistic assertion without introduction and in too unexpected a fashion is counterproductive, confusing, and can even be damaging. There may never be one, too. As Weinberg described it in 1995:[144]
The fact that the standards of scientific success shift with time does not only make the philosophy of science difficult; it also raises problems for the public understanding of science. We do not have a fixed scientific method to rally around and defend.
- ^ "The sociology of knowledge is concerned with "the relationship between human thought and the social context in which it arises."[158] So, on this reading, the sociology of science may be taken to be considered with the analysis of the social context of scientific thought. But scientific thought, most sociologists concede, is distinguished from other modes of thought precisely by virtue of its immunity from social determination — insofar as it is governed by reason rather than by tradition, and insofar as it is rational it escapes determination by "non-logical" social forces." — M. D. King leading into his article on Reason, tradition, and the progressiveness of science (1971)[159]
- ^ a b Stillwell's review (p. 381) of Poincaré's efforts on the Euler characteristic notes that it took five iterations for Poincaré to arrive at the Poincaré homology sphere.[186]
References
- ^ a b Newton, Isaac (1999) [1726 (3rd ed.)]. Philosophiæ Naturalis Principia Mathematica [Mathematical Principles of Natural Philosophy]. The Principia: Mathematical Principles of Natural Philosophy. Translated by Cohen, I. Bernard; Whitman, Anne; Budenz, Julia. Includes "A Guide to Newton's Principia" by I. Bernard Cohen, pp. 1–370. (The Principia itself is on pp. 371–946). Berkeley, CA: University of California Press. 791–796 ("Rules of Reasoning in Philosophy"); see also Philosophiæ Naturalis Principia Mathematica#Rules of Reason. ISBN 978-0-520-08817-7.
- ^ "scientific method", Oxford Dictionaries: British and World English, 2016, archived from the original on 2016-06-20, retrieved 2016-05-28
- ^ Oxford English Dictionary (3rd ed.). Oxford: Oxford University Press. 2014. Archived from the original on 2023-11-29. Retrieved 2018-05-31 – via OED Online.
- ^ a b c Peirce, Charles Sanders (1908). Wikisource. with added notes. Reprinted with previously unpublished part, Collected Papers v. 6, paragraphs 452–85, The Essential Peirce v. 2, pp. 434–450, and elsewhere. N.B. 435.30 'living institution': Hibbert J. mis-transcribed 'living institution': ("constitution" for "institution") . Hibbert Journal. 7: 90–112 – via
- ^ Popper (1959), p. 273.
- ^ a b Gauch (2003), p. 3: "The scientific method 'is often misrepresented as a fixed sequence of steps,' rather than being seen for what it truly is, 'a highly variable and creative process' (AAAS 2000:18). The claim here is that science has general principles that must be mastered to increase productivity and enhance perspective, not that these principles provide a simple and automated sequence of steps to follow."
- ^ a b Gauch (2003), p. 3.
- ^ William Whewell, History of Inductive Science (1837), and in Philosophy of Inductive Science (1840)
- ^ Elizabeth Asmis (1985) Epicurus' Scientific Method. Cornell University Press
- ^ Alhacen (c.1035) Treatise on Light (رسالة في الضوء) as cited in Shmuel Sambursky, ed. (1975) Physical thought from the Presocratics to the quantum physicists : an anthology, p.137
- ^ a b Smith (2010) Book 7, [4.28] p.270
- ^ Alhazen, Treatise on Light (رسالة في الضوء), translated into English from German by M. Schwarz, from "Abhandlung über das Licht" Archived 2019-12-30 at the Wayback Machine, J. Baarmann (editor and translator from Arabic to German, 1882) Zeitschrift der Deutschen Morgenländischen Gesellschaft Vol 36 as quoted in Sambursky (1975), p. 136.
- ^ a b c Hockney (2006), p. 240: "Truth is sought for its own sake. And those who are engaged upon the quest for anything for its own sake are not interested in other things. Finding the truth is difficult, and the road to it is rough." – Alhazen (Ibn Al-Haytham 965 – c. 1040) Critique of Ptolemy, translated by S. Pines, Actes X Congrès internationale d'histoire des sciences, Vol I Ithaca 1962, as quoted in Sambursky (1975), p. 139. (This quotation is from Alhazen's critique of Ptolemy's books Almagest, Planetary Hypotheses, and Ptolemy's Theory of Visual Perception: An English Translation of the Optics. Translated by A. Mark Smith. American Philosophical Society. 1996. ISBN 9780871698629. Archived from the original on 2023-11-29. Retrieved 2021-11-27.)
- ^ Alikuzai (2013), p. 154.
- ^ Rozhanskaya & Levinova (1996).
- ^ Bacon, Opus Majus, Bk.&VI.
- ^ Borlik (2011), p. 132.
- ^ Inwood, Stephen (2003). The Forgotten Genius : The biography of Robert Hooke (1635–1703). San Francisco: MacAdam/Cage Pub. pp. 112–116. ISBN 978-1-931561-56-3. OCLC 53006741.
- ^ Hooke, Robert (1705). "First general: The present state of natural philosophy and wherein it is deficient". In Waller, Richard (ed.). The posthumous works of Robert Hooke, M.D. S.R.S. Geom. Prof. Gresh. etc.
- ^ various papers (PDF). The optics of Giovan Battista della Porta (1535–1615): A Reassessment Workshop at Technical University of Berlin, 24–25 October 2014. Archived from the original (PDF) on 2018-05-27.
- ^ Kepler, Johannes (1604) Ad Vitellionem paralipomena, quibus astronomiae pars opticae traditur (Supplements to Witelo, in which the optical part of astronomy is treated)[c] as cited in Smith, A. Mark (June 2004). "What Is the History of Medieval Optics Really about?". Proceedings of the American Philosophical Society. 148 (2): 180–194. JSTOR 1558283. PMID 15338543.
- ^ a b Galileo Galilei (1638).
- ^ Sanches (1988).
- ^ Lisa Downing, Stanford Encyclopedia of Philosophy (Fall 2021) George Berkeley, 3.2.3 Scientific explanation
- ^ Margaret Atherton (ed.) 1999 The Empiricists
- ^ Godfrey-Smith (2003), p. 236.
- ^ a b c d Thurs (2011).
- ^ a b Achinstein, Peter (2004). "General Introduction". Science Rules: A Historical Introduction to Scientific Methods. Johns Hopkins University Press. pp. 1–5. ISBN 978-0-8018-7943-2.
- ^ a b c Cowles (2020), p. 264
- ^ a b Popper (1963). Conjectures and Refutations (PDF). pp. 312–365. Archived from the original (PDF) on 2017-10-13.
If we have made this our task, then there is no more rational procedure than the method of trial and error--of conjecture and refutation
- ^ a b Smolin, Lee (May 2013). "There is No Scientific Method". Archived from the original on 2016-08-07. Retrieved 2016-06-07.
- ^ a b Thurs, Daniel P. (2015), "That the scientific method accurately reflects what scientists actually do", in Numbers, Ronald L.; Kampourakis, Kostas (eds.), Newton's Apple and Other Myths about Science, Harvard University Press, pp. 210–218, ISBN 978-0-674-91547-3, archived from the original on 2023-11-29, retrieved 2020-10-20,
It's probably best to get the bad news out of the way first, the so-called scientific method is a myth. ... If typical formulations were accurate, the only location true science would be taking place in would be grade-school classrooms.
- ^ a b Mark Snyder (1984) When Belief Creates Reality Archived 2021-08-24 at the Wayback Machine Advances in Experimental Social Psychology Volume 18, 1984, Pages 247-305
- ^ a b Taleb (2007), p. 72 lists ways to avoid the narrative fallacy and confirmation bias; the narrative fallacy being a substitute for explanation.
- ^ Nola, Robert; Sankey, Howard (2007). Theories of Scientific Method: An Introduction. Philosophy and science. Vol. 2. Montréal: McGill–Queen's University Press. pp. 1, 300. doi:10.4324/9781315711959. ISBN 9780773533448. OCLC 144602109.
There is a large core of people who think there is such a thing as a scientific method that can be justified, although not all agree as to what this might be. But there are also a growing number of people who think that there is no method to be justified. For some, the whole idea is yesteryear's debate, the continuation of which can be summed up as yet more of the proverbial 'flogging a dead horse'. We beg to differ. ... We shall claim that Feyerabend did endorse various scientific values, did accept rules of method (on a certain understanding of what these are), and did attempt to justify them using a meta methodology somewhat akin to the principle of reflective equilibrium.
- ^ Staddon, John (1 December 2017). Scientific Method: How Science Works, Fails to Work, and Pretends to Work. New York: Routledge. doi:10.4324/9781315100708. ISBN 978-1-315-10070-8.
- ^ Staddon, John (16 September 2020). "Whatever Happened to History of Science?" (PDF). Archived (PDF) from the original on 2021-08-27. Retrieved 2021-08-27.
science is best understood through examples
- ^ a b "Philosophy [i.e., physics] is written in this grand book – I mean the universe – which stands continually open to our gaze, but it cannot be understood unless one first learns to comprehend the language and interpret the characters in which it is written. It is written in the language of mathematics, and its characters are triangles, circles, and other geometrical figures, without which it is humanly impossible to understand a single word of it; without these, one is wandering around in a dark labyrinth." – Galileo Galilei, Il Saggiatore (The Assayer, 1623), as translated by Stillman Drake (1957), Discoveries and Opinions of Galileo pp. 237–238, as quoted by di Francia (1981), p. 10.
- ^ Godfrey-Smith, Peter (2009). Theory and Reality: An Introduction to the Philosophy of Science. Chicago: University of Chicago Press. ISBN 978-0-226-30062-7. Archived from the original on 2023-11-29. Retrieved 2020-05-09.
- ^ a b Brody (1993), p. 10 calls this an epistemic cycle; these cycles can occur at high levels of abstraction.
- ^ a b Peirce, Charles Sanders (1877). Wikisource.. . Popular Science Monthly. 12: 1–15 – via
- ^ Peirce, Charles S., Collected Papers v. 5, in paragraph 582, from 1898: "... [rational] inquiry of every type, fully carried out, has the vital power of self-correction and of growth. This is a property so deeply saturating its inmost nature that it may truly be said that there is but one thing needful for learning the truth, and that is a hearty and active desire to learn what is true."
- ^ Einstein & Infeld (1938), p. 92: "To raise new questions, new possibilities, to regard old problems from a new angle, requires creative imagination and marks real advance in science."
- ^ Richard Westfall, (1983) Never At Rest
- ^ Crawford S, Stucki L (1990). "Peer review and the changing research record". Journal of the American Society for Information Science. 41 (3): 223–228. doi:10.1002/(SICI)1097-4571(199004)41:3<223::AID-ASI14>3.0.CO;2-3.
- ^ Gauch (2003), esp. chapters 5–8.
- ^ René Descartes (1637) Discourse on the Method/Part 2 Archived 2021-09-01 at the Wayback Machine Part II
- ^ McCarty (1985), p. 252.
- ^ McElheny (2004), p. 34.
- ^ Schuster, Daniel P.; Powers, William J., eds. (2005). "Ch. 1". Translational and Experimental Clinical Research. Lippincott Williams & Wilkins. ISBN 9780781755658. Archived from the original on 2023-11-29. Retrieved 2021-11-27. This chapter also discusses the different types of research questions and how they are produced.
- ^ Andreas Vesalius, Epistola, Rationem, Modumque Propinandi Radicis Chynae Decocti (1546), p. 141. Quoted and translated in C.D. O'Malley, Andreas Vesalius of Brussels, (1964), p. 116. As quoted by Bynum & Porter (2005), p. 597: "Andreas Vesalius"
- ^ Crick, Francis (1994), The Astonishing Hypothesis ISBN 0-684-19431-7 p. 20
- ^ McElheny (2004), p. 40: October 1951 — "That's what a helix should look like!" Crick exclaimed in delight (This is the Cochran-Crick-Vand-Stokes theory of the transform of a helix).
- ^ Judson (1979), p. 157. "'The structure that we propose is a three-chain structure, each chain being a helix' – Linus Pauling"
- ^ McElheny (2004), pp. 49–50: January 28, 1953 — Watson read Pauling's pre-print, and realized that in Pauling's model, DNA's phosphate groups had to be un-ionized. But DNA is an acid, which contradicts Pauling's model.
- ^ Einstein, Albert (1949). The World as I See It. New York: Philosophical Library. pp. 24–28.
- ^ Dewey (1910), p. 26
- ^ Aristotle (trans. 1853) Prior Analytics 2.25 Archived 2021-09-10 at the Wayback Machine via Wikisource
- ^ a b c d Peirce, Charles Sanders (1877). Wikisource. . Popular Science Monthly. 12: 286–302 – via
- ^ Glen (1994), pp. 37–38.
- ^ Platt, John R. (16 October 1964). "Strong Inference". Science. 146 (3642): 347–. Bibcode:1964Sci...146..347P. doi:10.1126/science.146.3642.347. PMID 17739513.
- ^ Leon Lederman, for teaching physics first, illustrates how to avoid confirmation bias: Ian Shelton, in Chile, was initially skeptical that supernova 1987a was real, but possibly an artifact of instrumentation (null hypothesis), so he went outside and disproved his null hypothesis by observing SN 1987a with the naked eye. The Kamiokande experiment, in Japan, independently observed neutrinos from SN 1987a at the same time.
- ^ Judson (1979), pp. 137–138: "Watson did enough work on Tobacco mosaic virus to produce the diffraction pattern for a helix, per Crick's work on the transform of a helix."
- ^ McElheny (2004), p. 43: June 1952 — Watson had succeeded in getting X-ray pictures of TMV showing a diffraction pattern consistent with the transform of a helix.
- ^ Cochran W, Crick FHC and Vand V. (1952) "The Structure of Synthetic Polypeptides. I. The Transform of Atoms on a Helix", Acta Crystallogr., 5, 581–586.
- ^ McElheny (2004), p. 68: Nature April 25, 1953.
- ^ In March 1917, the Royal Astronomical Society announced that on May 29, 1919, the occasion of a total eclipse of the sun would afford favorable conditions for testing Einstein's General theory of relativity. One expedition, to Sobral, Ceará, Brazil, and Eddington's expedition to the island of Principe yielded a set of photographs, which, when compared to photographs taken at Sobral and at Greenwich Observatory showed that the deviation of light was measured to be 1.69 arc-seconds, as compared to Einstein's desk prediction of 1.75 arc-seconds. – Antonina Vallentin (1954), Einstein, as quoted by Samuel Rapport and Helen Wright (1965), Physics, New York: Washington Square Press, pp. 294–295.
- ^ "The Secret of Photo 51". NOVA. PBS. Archived from the original on 2017-08-31. Retrieved 2017-09-11.
- ^ a b Cynthia Wolberger (2021) Photograph 51 explained
- ^ a b McElheny (2004), p. 52: Friday, January 30, 1953. Tea time — Franklin confronts Watson and his paper – "Of course it [Pauling's pre-print] is wrong. DNA is not a helix." However, Watson then visits Wilkins' office, sees photo 51, and immediately recognizes the diffraction pattern of a helical structure. But additional questions remained, requiring additional iterations of their research. For example, the number of strands in the backbone of the helix (Crick suspected 2 strands, but cautioned Watson to examine that more critically), the location of the base pairs (inside the backbone or outside the backbone), etc. One key point was that they realized that the quickest way to reach a result was not to continue a mathematical analysis, but to build a physical model. Later that evening — Watson urges Wilkins to begin model-building immediately. But Wilkins agrees to do so only after Franklin's departure.
- ^ Watson (1968), p. 167: "The instant I saw the picture my mouth fell open and my pulse began to race." Page 168 shows the X-shaped pattern of the B-form of DNA, clearly indicating crucial details of its helical structure to Watson and Crick.
- ^ a b c Peirce, Charles S. (1902), Carnegie application, see MS L75.329330, from Draft D Archived 2011-05-24 at the Wayback Machine of Memoir 27: "Consequently, to discover is simply to expedite an event that would occur sooner or later, if we had not troubled ourselves to make the discovery. Consequently, the art of discovery is purely a question of economics. The economics of research is, so far as logic is concerned, the leading doctrine concerning the art of discovery. Consequently, the conduct of abduction, which is chiefly a question of heuretic and is the first question of heuretic, is to be governed by economical considerations."
- ^ a b c d Peirce, Charles S. (1899). "F.R.L. [First Rule of Logic]". Collected Papers. v. 1. paragraphs 135–140. Archived from the original on 2012-01-06. Retrieved 2012-01-06.
... in order to learn, one must desire to learn ...
- ^ a b c McElheny (2004), pp. 57–59: Saturday, February 28, 1953 — Watson found the base-pairing mechanism which explained Chargaff's rules using his cardboard models.
- ^ Mill, John Stuart, "A System of Logic", University Press of the Pacific, Honolulu, 2002, ISBN 1-4102-0252-6.
- ^ a b c d MacKay, Donald M. (1969). Information, Mechanism, and Meaning. Cambridge, MA: MIT Press. pp. 1–4. ISBN 0-262-63032-X.
Invariably one came up against fundamental physical limits to the accuracy of measurement. ... The art of physical measurement seemed to be a matter of compromise, of choosing between reciprocally related uncertainties. ... Multiplying together the conjugate pairs of uncertainty limits mentioned, however, I found that they formed invariant products of not one but two distinct kinds. ... The first group of limits were calculable a priori from a specification of the instrument. The second group could be calculated only a posteriori from a specification of what was done with the instrument. ... In the first case each unit [of information] would add one additional dimension (conceptual category), whereas in the second each unit would add one additional atomic fact.
- ^ National Science Foundation (NSF) (2021) NSF Reports Archived 2021-08-17 at the Wayback Machine and News Archived 2021-08-20 at the Wayback Machine
- ^ "LHC long term schedule". lhc-commissioning.web.cern.ch. Archived from the original on 2020-04-25. Retrieved 2021-08-22. (2021)
- ^ "ligo.caltech.edu (1999) Laser Interferometer Gravitational-Wave Observatory". Archived from the original on 2021-09-01. Retrieved 2021-08-30.
- ^ "NIF (2021) What Is the National Ignition Facility?". Archived from the original on 2017-07-31. Retrieved 2021-08-22.
- ^ "ISS (2021) International Space Station". 12 January 2015. Archived from the original on 2005-09-07. Retrieved 2021-08-22.
- ^ "JWST (2021) WEBB Space Telescope". Archived from the original on 2012-01-04. Retrieved 2021-08-22.
- ^ James Webb Space Telescope (JWST) (12 Nov 2021) James Webb Space Telescope Deployment Sequence (Nominal) Archived 2021-12-23 at the Wayback Machine highlights the predictions from launch to day+29,
- ^ "James Crutchfield (2003) "Complex Systems Theory?"" (PDF). Archived (PDF) from the original on 2021-04-18. Retrieved 2018-05-27.
- ^ al-Battani, De Motu Stellarum translation from Arabic to Latin in 1116, as cited by E. S. Kennedy, A Survey of Islamic Astronomical Tables, (Transactions of the American Philosophical Society, New Series, 46, 2), Philadelphia, 1956, pp. 10–11, 32–34.
- ^ a b Smith (2001b).
- ^ Smith (2010), p. 220 Book Seven covers refraction.
- ^ McElheny (2004), p. 53: The weekend (January 31 – February 1) — After seeing photo 51, Watson informed Bragg of the X-ray diffraction image of DNA in B form. Bragg permitted them to restart their research on DNA (that is, model building).
- ^ McElheny (2004), p. 54: Sunday, February 8, 1953 — Maurice Wilkes gave Watson and Crick permission to work on models, as Wilkes would not be building models until Franklin left DNA research.
- ^ McElheny (2004), p. 56: Jerry Donohue, on sabbatical from Pauling's lab and visiting Cambridge, advises Watson that the textbook form of the base pairs was incorrect for DNA base pairs; rather, the keto form of the base pairs should be used instead. This form allowed the bases' hydrogen bonds to pair 'unlike' with 'unlike', rather than to pair 'like' with 'like', as Watson was inclined to model, based on the textbook statements. On February 27, 1953, Watson was convinced enough to make cardboard models of the nucleotides in their keto form.
- ^ Watson (1968), pp. 194–197: "Suddenly I became aware that an adenine-thymine pair held together by two hydrogen bonds was identical in shape to a guanine-cytosine pair held together by at least two hydrogen bonds. ..."
- ^ McElheny (2004), p. 57: Saturday, February 28, 1953 — Watson tried 'like with like' and admitted these base pairs didn't have hydrogen bonds that line up. But after trying 'unlike with unlike', and getting Jerry Donohue's approval, the base pairs turned out to be identical in shape (as Watson stated above in his 1968 Double Helix memoir quoted above). Watson now felt confident enough to inform Crick. (Of course, 'unlike with unlike' increases the number of possible codons, if this scheme were a genetic code.)
- ^ Goldstein, Bernard R. (1977) Ibn Mu'adh's "(1079) Treatise On Twilight and the Height of the Atmosphere Archived 2022-09-21 at the Wayback Machine" Archive for History of Exact Sciences Vol. 17, No. 2 (21.VII.1977), pp. 97-118 (22 pages) JSTOR. (Treatise On Twilight was printed by F Risner in Opticae Thesaurus (1572) as Liber de crepusculis, but attributed to Alhazen rather than Ibn Mu'adh.)
- ^ Karl Raimund Popper (2002). The logic of scientific discovery (Reprint of translation of 1935 Logik der Forschung ed.). Routledge/Taylor & Francis Group. pp. 18, 280. ISBN 0415278430.
- ^ Karl Popper. "Science: Conjectures and refutations" (PDF). Texas A&M University The motivation & cognition interface lab. Archived from the original (PDF) on 2013-09-09. Retrieved 2013-01-22. This lecture by Popper was first published as part of the book Conjectures and Refutations and is linked here.
- ^ Needham & Wang (1954), p. 166 shows how the 'flying gallop' image propagated from China to the West.
- ^ Goldhaber & Nieto (2010), p. 940.
- ^ Ronald R. Sims (2003). Ethics and corporate social responsibility: Why giants fall. p. 21: "'A myth is a belief given uncritical acceptance by members of a group ...' – Weiss, Business Ethics p. 15."
- ^ a b Goldhaber & Nieto (2010), p. 942.
- ^ Lakatos (1976), pp. 1–19.
- ^ Krider, E. Philip (January 2006). "Benjamin Franklin and lightning rods". Physics Today. 59 (1): 42. Bibcode:2006PhT....59a..42K. doi:10.1063/1.2180176. S2CID 110623159.
On 6 August 1753, the Swedish scientist Georg Wilhelm Richmann was electrocuted in St. Petersburg ...
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Gauch gives two simplified statements on what he calls "rational-knowledge claim". It is either "I hold belief X for reasons R with level of confidence C, where inquiry into X is within the domain of competence of method M that accesses the relevant aspects of reality" (inductive reasoning) or "I hold belief X because of presuppositions P." (deductive reasoning)
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- ^ Brad Snowder's Astronomy Pages ( Precession of the Equinox
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The [philosophical] study of scientific method is the attempt to discern the activities by which [the success of science] is achieved. Among the activities often identified as characteristic of science are systematic observation and experimentation, inductive and deductive reasoning, and the formation and testing of hypotheses and theories.
- ^ Hempel, Carl Gustav (1966). Philosophy Of Natural Science. p. 7. Retrieved 2024-04-30. Hempel illustrates this at Semmelweiss’ experiments with childbed fever.
- ^ Gauch (2003), p. 159.
- ^ Thomas Kuhn formally stated this need for the "norms for rational theory choice". One of his discussions is reprinted in Thomas S Kuhn (1 November 2002). "Chapter 9: Rationality and Theory Choice". In James Conant, John Haugeland (ed.). The Road since Structure: Philosophical Essays, 1970–1993 (2nd ed.). University of Chicago Press. pp. 208 ff. ISBN 0226457990.
- ^ Kuhn, T.S. (1977) Objectivity, Value Judgment, and Theory Choice. In: Kuhn, T.S., Ed., The Essential Tension—Selected Studies in Scientific Tradition and Change, The University of Chicago Press, Chicago, 320-339.
- ^ a b Mark Colyvan (2001). The Indispensability of Mathematics. Oxford University Press. pp. 78–79. ISBN 0195166612.
- ^ a b c Weinert, Friedel (2004). "Invariance and reality". The Scientist as Philosopher: Philosophical Consequences of Great Scientific Discoveries. Berlin; New York: Springer-Verlag. pp. 62–74 (72). doi:10.1007/b138529. ISBN 3540205802. OCLC 53434974.
- ^ a b Deutsch, David (October 2009). A new way to explain explanation. TED talk. Event occurs at 15:05min. Archived from the original on 2018-11-04. Retrieved 2018-09-16. Also available from YouTube Archived 8 November 2022 at the Wayback Machine.
- ^ a b c Stephen Hawking; Leonard Mlodinow (2010). "What is reality?". The Grand Design. Random House Digital, Inc. pp. 51–52. ISBN 978-0553907070. See also: model-dependent realism.
- ^ a b c Baker, Alan (25 February 2010). "Simplicity". In Edward N. Zalta (ed.). The Stanford Encyclopedia of Philosophy (Summer 2011 Edition).
- ^ Bird, Alexander (11 August 2011). "§4.1 Methodological Incommensurability". In Edward N. Zalta (ed.). The Stanford Encyclopedia of Philosophy (Spring 2013 Edition).
- ^
See Stephen Hawking; Leonard Mlodinow (2010). The Grand Design. Random House Digital, Inc. p. 8. ISBN 978-0553907070.
It is a whole family of different theories, each of which is a good description of observations only in some range of physical situations...But just as there is no map that is a good representation of the earth's entire surface, there is no single theory that is a good representation of observations in all situations.
- ^
E Brian Davies (2006). "Epistemological pluralism". PhilSci Archive. p. 4.
Whatever might be the ultimate goals of some scientists, science, as it is currently practised, depends on multiple overlapping descriptions of the world, each of which has a domain of applicability. In some cases this domain is very large, but in others quite small.
- ^ Gauch (2003), p. 269.
- ^ Gauch Jr, Hugh G. (12 December 2002). Scientific Method in Practice. Cambridge University Press. p. 33. doi:10.1017/cbo9780511815034.011. ISBN 978-0-521-81689-2.
- ^ Welsby, Philip D; Weatherall, Mark (1 October 2022). "Statistics: an introduction to basic principles". Postgraduate Medical Journal. 98 (1164): 793–798. doi:10.1136/postgradmedj-2020-139446. ISSN 0032-5473. PMID 34039698.
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- ^ Gigerenzer, Gerd (31 March 2015). Risk Savvy. New York, New York: Penguin. ISBN 978-0-14-312710-9. leads: (n=1000) only 21% of gynaecologists got an example question on Bayes' theorem right. Book, including the assertion, introduced in Kremer, William (6 July 2014). "Do doctors understand test results?". BBC News. Retrieved 2024-04-24.
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- ^ As cited in Fleck (1979), p. 27, Fleck (1979), pp. 38–50
- ^ Fleck (1979), p. xxviii
- ^ Fleck (1979), p. 27
- ^ Kuhn, Thomas S. (2009). The Structure of Scientific Revolutions. Chicago, IL: University of Chicago Press. p. 113. ISBN 978-1-4432-5544-8.
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- Fashionable Nonsense: Postmodern Intellectuals' Abuse of Science, Picador. 1999
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- A House Built on Sand: Exposing Postmodernist Myths About Science, Oxford University Press, 2000
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- ^ Ludwik Fleck (1979) Genesis and Development of a Scientific Fact Archived 2021-08-26 at the Wayback Machine
- ^ Pólya (1957), p. 131 in the section on 'Modern heuristic': "When we are working intensively, we feel keenly the progress of our work; we are elated when our progress is rapid, we are depressed when it is slow."
- ^ Huai-Dong Cao and Xi-Ping Zhu (3 Dec 2006) Hamilton-Perelman’s Proof of the Poincaré Conjecture and the Geometrization Conjecture
- revised from H.D.Cao and X.P.Zhu Asian J. Math., 10(2) (2006), 165–492.
- ^ George Lakoff and Rafael E. Núñez (2000) Where Mathematics Comes From
- ^ "If you can't solve a problem, then there is an easier problem you can solve: find it." —Pólya (1957), p. 114
- ^ George Pólya (1954), Mathematics and Plausible Reasoning Volume I: Induction and Analogy in Mathematics.
- ^ George Pólya (1954), Mathematics and Plausible Reasoning Volume II: Patterns of Plausible Reasoning.
- ^ Pólya (1957), p. 142.
- ^ Pólya (1957), p. 144.
- ^ Lakatos (1976) documents the development, by generations of mathematicians, of Euler's formula for polyhedra.
- ^ H.S.M. Coxeter (1973) Regular Polytopes ISBN 9780486614809, Chapter IX "Poincaré's proof of Euler's formula"
- ^ "Charles A. Weibel (ca. 1995) History of Homological Algebra" (PDF). Archived (PDF) from the original on 2021-09-06. Retrieved 2021-08-28.
- ^ Henri Poincaré, Sur l’analysis situs, Comptes rendusde l’Academie des Sciences 115 (1892), 633–636. as cited by Lakatos (1976), p. 162
- ^ John Stillwell, reviewer (Apr 2014). Notices of the AMS. 61 (4), pp. 378–383, on Jeremy Gray's (2013) Henri Poincaré: A Scientific Biography (PDF Archived 2021-07-04 at the Wayback Machine).
- ^ Lakatos (1976), p. 55.
- ^ Mackay (1991), p. 100.
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Further reading
- Bauer, Henry H., Scientific Literacy and the Myth of the Scientific Method, University of Illinois Press, Champaign, IL, 1992
- Beveridge, William I.B., The Art of Scientific Investigation, Heinemann, Melbourne, Australia, 1950.
- Bernstein, Richard J., Beyond Objectivism and Relativism: Science, Hermeneutics, and Praxis, University of Pennsylvania Press, Philadelphia, PA, 1983.
- Brody, Baruch A. and Capaldi, Nicholas, Science: Men, Methods, Goals: A Reader: Methods of Physical Science Archived 2023-04-13 at the Wayback Machine, W.A. Benjamin, 1968
- Brody, Baruch A. and Grandy, Richard E., Readings in the Philosophy of Science, 2nd edition, Prentice-Hall, Englewood Cliffs, NJ, 1989.
- Burks, Arthur W., Chance, Cause, Reason: An Inquiry into the Nature of Scientific Evidence, University of Chicago Press, Chicago, IL, 1977.
- Chalmers, Alan, What Is This Thing Called Science?. Queensland University Press and Open University Press, 1976.
- Crick, Francis (1988), What Mad Pursuit: A Personal View of Scientific Discovery, New York: Basic Books, ISBN 978-0-465-09137-9.
- Crombie, A.C. (1953), Robert Grosseteste and the Origins of Experimental Science 1100–1700, Oxford: Clarendon
- Earman, John (ed.), Inference, Explanation, and Other Frustrations: Essays in the Philosophy of Science, University of California Press, Berkeley & Los Angeles, CA, 1992.
- Fraassen, Bas C. van, The Scientific Image, Oxford University Press, Oxford, 1980.
- Franklin, James (2009), What Science Knows: And How It Knows It, New York: Encounter Books, ISBN 978-1-59403-207-3.
- Gadamer, Hans-Georg, Reason in the Age of Science, Frederick G. Lawrence (trans.), MIT Press, Cambridge, MA, 1981.
- Giere, Ronald N. (ed.), Cognitive Models of Science, vol. 15 in 'Minnesota Studies in the Philosophy of Science', University of Minnesota Press, Minneapolis, MN, 1992.
- Hacking, Ian, Representing and Intervening, Introductory Topics in the Philosophy of Natural Science, Cambridge University Press, Cambridge, 1983.
- Heisenberg, Werner, Physics and Beyond, Encounters and Conversations, A.J. Pomerans (trans.), Harper and Row, New York, 1971, pp. 63–64.
- Holton, Gerald, Thematic Origins of Scientific Thought: Kepler to Einstein, 1st edition 1973, revised edition, Harvard University Press, Cambridge, MA, 1988.
- Karin Knorr Cetina, Knorr Cetina, Karin (1999). Epistemic cultures: how the sciences make knowledge. Cambridge, Massachusetts: Harvard University Press. ISBN 978-0-674-25894-5.
- Kuhn, Thomas S., The Essential Tension, Selected Studies in Scientific Tradition and Change, University of Chicago Press, Chicago, IL, 1977.
- Latour, Bruno, Science in Action, How to Follow Scientists and Engineers through Society, Harvard University Press, Cambridge, MA, 1987.
- Losee, John, A Historical Introduction to the Philosophy of Science, Oxford University Press, Oxford, 1972. 2nd edition, 1980.
- Maxwell, Nicholas, The Comprehensibility of the Universe: A New Conception of Science, Oxford University Press, Oxford, 1998. Paperback 2003.
- Maxwell, Nicholas, Understanding Scientific Progress Archived 2018-02-20 at the Wayback Machine, Paragon House, St. Paul, Minnesota, 2017.
- McComas, William F., ed. (1998). "The Principal Elements of the Nature of Science: Dispelling the Myths" (PDF). The Nature of Science in Science Education. Netherlands: Kluwer Academic Publishers. pp. 53–70. Archived from the original (PDF) on 2014-07-01.
- Misak, Cheryl J., Truth and the End of Inquiry, A Peircean Account of Truth, Oxford University Press, Oxford, 1991.
- Oreskes, Naomi, "Masked Confusion: A trusted source of health information misleads the public by prioritizing rigor over reality", Scientific American, vol. 329, no. 4 (November 2023), pp. 90–91.
- Piattelli-Palmarini, Massimo (ed.), Language and Learning, The Debate between Jean Piaget and Noam Chomsky, Harvard University Press, Cambridge, MA, 1980.
- Popper, Karl R., Unended Quest, An Intellectual Autobiography, Open Court, La Salle, IL, 1982.
- Putnam, Hilary, Renewing Philosophy, Harvard University Press, Cambridge, MA, 1992.
- Rorty, Richard, Philosophy and the Mirror of Nature, Princeton University Press, Princeton, NJ, 1979.
- Salmon, Wesley C., Four Decades of Scientific Explanation, University of Minnesota Press, Minneapolis, MN, 1990.
- Shimony, Abner, Search for a Naturalistic World View: Vol. 1, Scientific Method and Epistemology, Vol. 2, Natural Science and Metaphysics, Cambridge University Press, Cambridge, 1993.
- Thagard, Paul, Conceptual Revolutions, Princeton University Press, Princeton, NJ, 1992.
- Ziman, John (2000). Real Science: what it is, and what it means. Cambridge: Cambridge University Press.
External links
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- Andersen, Hanne; Hepburn, Brian. "Scientific Method". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy.
- "Confirmation and Induction". Internet Encyclopedia of Philosophy.
- Scientific method at PhilPapers
- Scientific method at the Indiana Philosophy Ontology Project
- An Introduction to Science: Scientific Thinking and a scientific method Archived 2018-01-01 at the Wayback Machine by Steven D. Schafersman.
- Introduction to the scientific method at the University of Rochester
- The scientific method from a philosophical perspective
- Theory-ladenness by Paul Newall at The Galilean Library
- Lecture on Scientific Method by Greg Anderson (archived 28 April 2006)
- Using the scientific method for designing science fair projects
- Scientific Methods an online book by Richard D. Jarrard
- Richard Feynman on the Key to Science (one minute, three seconds), from the Cornell Lectures.
- Lectures on the Scientific Method by Nick Josh Karean, Kevin Padian, Michael Shermer and Richard Dawkins (archived 21 January 2013).
- "How Do We Know What Is True?" (animated video; 2:52)