# kb

id: scientific-law-20260505-3
file: data/en.wikipedia.org/wiki/Scientific_law-3.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:17:34.904998+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
in which the (more famous) mass–energy equivalence E = mc2 is a special case. General relativity: General relativity is governed by the Einstein field equations, which describe the curvature of space-time due to mass-energy equivalent to the gravitational field. Solving the equation for the geometry of space warped due to the mass distribution gives the metric tensor. Using the geodesic equation, the motion of masses falling along the geodesics can be calculated. Gravitoelectromagnetism: In a relatively flat spacetime due to weak gravitational fields, gravitational analogues of Maxwell's equations can be found; the GEM equations, to describe an analogous gravitomagnetic field. They are well established by the theory, and experimental tests form ongoing research. ==== Classical laws ==== Kepler's laws, though originally discovered from planetary observations (also due to Tycho Brahe), are true for any central forces. === Thermodynamics === Newton's law of cooling Fourier's law Ideal gas law, combines a number of separately developed gas laws; Boyle's law Charles's law Gay-Lussac's law Avogadro's law, into one now improved by other equations of state Dalton's law (of partial pressures) Boltzmann equation Carnot's theorem Kopp's law === Electromagnetism === Maxwell's equations give the time-evolution of the electric and magnetic fields due to


id: scientific-law-20260505-4
file: data/en.wikipedia.org/wiki/Scientific_law-4.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:17:34.904998+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
In equilibrium, molecules exist in mixture defined by the transformations possible on the timescale of the equilibrium, and are in a ratio defined by the intrinsic energy of the molecules—the lower the intrinsic energy, the more abundant the molecule. Le Chatelier's principle states that the system opposes changes in conditions from equilibrium states, i.e. there is an opposition to change the state of an equilibrium reaction. Transforming one structure to another requires the input of energy to cross an energy barrier; this can come from the intrinsic energy of the molecules themselves, or from an external source which will generally accelerate transformations. The higher the energy barrier, the slower the transformation occurs. There is a hypothetical intermediate, or transition structure, that corresponds to the structure at the top of the energy barrier. The Hammond–Leffler postulate states that this structure looks most similar to the product or starting material which has intrinsic energy closest to that of the energy barrier. Stabilizing this hypothetical intermediate through chemical interaction is one way to achieve catalysis. All chemical processes are reversible (law of microscopic reversibility) although some processes have such an energy bias, they are essentially irreversible. The reaction rate has the mathematical parameter


id: scientific-law-20260505-5
file: data/en.wikipedia.org/wiki/Scientific_law-5.md
category: reference
title: Scientific law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_law
date_saved: 2026-05-05T03:17:34.904998+00:00
instance: kb-cron
parent: scientific-law-20260505-0
summary:
In Europe, systematic theorizing about nature (physis) began with the early Greek philosophers and scientists and continued into the Hellenistic and Roman imperial periods, during which times the intellectual influence of Roman law increasingly became paramount.The formula "law of nature" first appears as "a live metaphor" favored by Latin poets Lucretius, Virgil, Ovid, Manilius, in time gaining a firm theoretical presence in the prose treatises of Seneca and Pliny. Why this Roman origin? According to [historian and classicist Daryn] Lehoux's persuasive narrative, the idea was made possible by the pivotal role of codified law and forensic argument in Roman life and culture. For the Romans ... the place par excellence where ethics, law, nature, religion and politics overlap is the law court. When we read Seneca's Natural Questions, and watch again and again just how he applies standards of evidence, witness evaluation, argument and proof, we can recognize that we are reading one of the great Roman rhetoricians of the age, thoroughly immersed in forensic method. And not Seneca alone. Legal models of scientific judgment turn up all over the place, and for example prove equally integral to Ptolemy's approach to verification, where the mind is assigned the role of


id: scientific-priority-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_priority-0.md
category: reference
title: Scientific priority
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_priority
date_saved: 2026-05-05T03:17:36.061644+00:00
instance: kb-cron
parent: scientific-priority-20260505-0
summary:
In science, priority is the credit given to the individual or group of individuals who first made the discovery or proposed the theory. Fame and honours usually go to the first person or group to publish a new finding, even if several researchers arrived at the same conclusion independently and at the same time. Thus, between two or more independent discoverers, the first to publish is the legitimate winner. Hence, the tradition is often referred to as the priority rule, the procedure of which can be summed up in the phrase "publish or perish", because there are generally no prizes for second place in science academia. In a way, the race to be first inspires risk-taking that can lead to scientific breakthroughs which is beneficial to the society (such as discovery of malaria transmission, DNA, HIV, etc.). On the other hand, it can create unhealthy competition and incentives to publish low-quality findings (e.g., quantity over quality or committing scientific misconduct), which can lead to an unreliable published literature and harm scientific progress. == Priority disputes == Priority becomes a difficult issue usually in the context of priority disputes, where the priority for a given theory, understanding, or discovery comes into


id: scientific-protocol-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_protocol-0.md
category: reference
title: Scientific protocol
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_protocol
date_saved: 2026-05-05T03:17:37.385028+00:00
instance: kb-cron
parent: scientific-protocol-20260505-0
summary:
In natural and social science research, a protocol is most commonly a predefined procedural method in the design and implementation of an experiment. Protocols are written whenever it is desirable to standardize a laboratory method to ensure successful replication of results by others in the same laboratory or by other laboratories. Additionally, and by extension, protocols have the advantage of facilitating the assessment of experimental results through peer review. In addition to detailed procedures, equipment, and instruments, protocols will also contain study objectives, reasoning for experimental design, reasoning for chosen sample sizes, safety precautions, and how results were calculated and reported, including statistical analysis and any rules for predefining and documenting excluded data to avoid bias. Similarly, a protocol may refer to the procedural methods of health organizations, commercial laboratories, manufacturing plants, etc. to ensure their activities (e.g., blood testing at a hospital, testing of certified reference materials at a calibration laboratory, and manufacturing of transmission gears at a facility) are consistent to a specific standard, encouraging safe use and accurate results. Finally, in the field of social science, a protocol may also refer to a "descriptive record" of observed events or a "sequence of behavior" of one or more


id: scientific-study-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_study-0.md
category: reference
title: Scientific study
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_study
date_saved: 2026-05-05T03:17:38.701672+00:00
instance: kb-cron
parent: scientific-study-20260505-0
summary:
Scientific study is a creative action to increase knowledge by systematically collecting, interpreting, and evaluating data. According to the hypothetico-deductive paradigm, it should encompass: The contextualization of the problem; A hypothesis for explaining the problem considering existing theoretical approaches; A verification of the hypotheses by an experiment; Analysis of the test outcome. Scientific study involves scientific theory, scientific method, scientific models, experiments and physical situations. It may refer to: Scientific method, a body of techniques for investigating phenomena, based on empirical or measurable evidence that is subject to the principles of logic and reasoning Observational study, draws inferences about the possible effect of a treatment on subjects, where the assignment of subjects into a treated group versus a control group is outside the control of the investigator Randomized controlled trial, a type of scientific experiment, often in the medical field, where the people being studied are randomly allocated one of the different treatments Science, a systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe. Scientific learning includes testing of theories and provide a basis for scientific knowledge. == History == Aristotle is believed to be the first to begin the study


id: scientific-temper-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_temper-0.md
category: reference
title: Scientific temper
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_temper
date_saved: 2026-05-05T03:17:40.005469+00:00
instance: kb-cron
parent: scientific-temper-20260505-0
summary:
The term scientific temper is broadly defined as "a modest open-minded temper—develop new light, new knowledge, new experiments, even when their results are unfavourable to preconceived opinions and long-cherished theories." It is a way of life (defined in this context as an individual and social process of thinking and acting) which uses the scientific method and which may, consequently, include questioning, observing physical reality, testing, hypothesizing, analyzing, and communicating (not necessarily in that order). Discussion, argument and analysis are vital parts of scientific temper. It aims to inculcate the values of scientific thinking, appreciate scientific development, and drive away superstition, religious bigotry, and all forms of pseudo-science. == Development of Scientific Temperament in World == Scientific temper as a notion existed for a long time, and the origin of the term is unknown. The exact terminology became frequently used in the mid-19th century. A Jesuit scholar Thomas Aloysius Hughes gave a short definition in 1893, saying, "A scientific temper... means a scrupulous and rigid exactness... [which] is the outcome of exact science." In his Conway Memorial Lecture in 1922, Bertrand Russell used the example of Albert Einstein to explain the meaning of scientific temper:We have had in recent years a


id: scientific-theory-20260505-0
file: data/en.wikipedia.org/wiki/Scientific_theory-0.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:17:41.183216+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
A scientific theory is an explanation of an aspect of the natural world that can be or that has been repeatedly tested and has corroborating evidence in accordance with the scientific method, using accepted protocols of observation, measurement, and evaluation of results. Where possible, theories are tested under controlled conditions in an experiment. In circumstances not amenable to experimental testing, theories are evaluated through principles of abductive reasoning. Established scientific theories have withstood rigorous scrutiny and embody scientific knowledge. A scientific theory differs from a scientific fact: a fact is an observation, while a theory connects and explains multiple observations. Furthermore, a theory is expected to make predictions which could be confirmed or refuted with additional observations. Stephen Jay Gould wrote that: "...facts and theories are different things, not rungs in a hierarchy of increasing certainty. Facts are the world's data. Theories are structures of ideas that explain and interpret facts." A theory differs from a scientific law in that a law is an empirical description of a relationship between facts and/or other laws. For example, Newton's Law of Gravity is a mathematical equation that can be used to predict the attraction between bodies, but it is not a theory


id: scientific-theory-20260505-1
file: data/en.wikipedia.org/wiki/Scientific_theory-1.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:17:41.183216+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
It can be subjected to minor adaptations to account for new data that do not fit it perfectly, as they are discovered, thus increasing its predictive capability over time. It is among the most parsimonious explanations, economical in the use of proposed entities or explanatory steps as per Occam's razor. This is because for each accepted explanation of a phenomenon, there may be an extremely large, perhaps even incomprehensible, number of possible and more complex alternatives, because one can always burden failing explanations with ad hoc hypotheses to prevent them from being falsified; therefore, simpler theories are preferable to more complex ones because they are more testable. === Definitions from scientific organizations === The United States National Academy of Sciences defines scientific theories as follows: The formal scientific definition of theory is quite different from the everyday meaning of the word. It refers to a comprehensive explanation of some aspect of nature that is supported by a vast body of evidence. Many scientific theories are so well established that no new evidence is likely to alter them substantially. For example, no new evidence will demonstrate that the Earth does not orbit around the Sun (heliocentric theory), or that living things


id: scientific-theory-20260505-2
file: data/en.wikipedia.org/wiki/Scientific_theory-2.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:17:41.183216+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
== Modification and improvement == If experimental results contrary to a theory's predictions are observed, scientists first evaluate whether the experimental design was sound, and if so they confirm the results by independent replication. A search for potential improvements to the theory then begins. Solutions may require minor or major changes to the theory, or none at all if a satisfactory explanation is found within the theory's existing framework. Over time, as successive modifications build on top of each other, theories consistently improve and greater predictive accuracy is achieved. Since each new version of a theory (or a completely new theory) must have more predictive and explanatory power than the last, scientific knowledge consistently becomes more accurate over time. If modifications to the theory or other explanations seem to be insufficient to account for the new results, then a new theory may be required. Since scientific knowledge is usually durable, this occurs much less commonly than modification. Furthermore, until such a theory is proposed and accepted, the previous theory will be retained. This is because it is still the best available explanation for many other phenomena, as verified by its predictive power in other contexts. For example, it has been


id: scientific-theory-20260505-3
file: data/en.wikipedia.org/wiki/Scientific_theory-3.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:17:41.183216+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
=== Theories and facts === A scientific theory does not turn into a fact. Scientific facts are observations that theories organize and explain. As new facts appear, a theory may be revised or new theories may emerge that encompass these additional facts. While American vernacular speech uses "theory" as similar to a "guess" in opposition to a "fact", in science the word "theory" means a model that is expected to explain a wide range of facts. == About theories == === Theories as axioms === The logical positivists thought of scientific theories as statements in a formal language. First-order logic is an example of a formal language. The logical positivists envisaged a similar scientific language. In addition to scientific theories, the language also included observation sentences ("the sun rises in the east"), definitions, and mathematical statements. The phenomena explained by the theories, if they could not be directly observed by the senses (for example, atoms and radio waves), were treated as theoretical concepts. In this view, theories function as axioms: predicted observations are derived from the theories much like theorems are derived in Euclidean geometry. However, the predictions are then tested against reality to verify the predictions, and the "axioms"


id: scientific-theory-20260505-4
file: data/en.wikipedia.org/wiki/Scientific_theory-4.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:17:41.183216+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
...it is incorrect to speak of an assumption as either true or false, since there is no way of proving it to be either (If there were, it would no longer be an assumption). It is better to consider assumptions as either useful or useless, depending on whether deductions made from them correspond to reality...Since we must start somewhere, we must have assumptions, but at least let us have as few assumptions as possible. Certain assumptions are necessary for all empirical claims (e.g. the assumption that reality exists). However, theories do not generally make assumptions in the conventional sense (statements accepted without evidence). While assumptions are often incorporated during the formation of new theories, these are either supported by evidence (such as from previously existing theories) or the evidence is produced in the course of validating the theory. This may be as simple as observing that the theory makes accurate predictions, which is evidence that any assumptions made at the outset are correct or approximately correct under the conditions tested. Conventional assumptions, without evidence, may be used if the theory is only intended to apply when the assumption is valid (or approximately valid). For example, the special theory of relativity


id: scientific-theory-20260505-5
file: data/en.wikipedia.org/wiki/Scientific_theory-5.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:17:41.183216+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
It is easy to obtain confirmations, or verifications, for nearly every theory—if we look for confirmations. Confirmations should count only if they are the result of risky predictions; that is to say, if, unenlightened by the theory in question, we should have expected an event which was incompatible with the theory—an event which would have refuted the theory. Every "good" scientific theory is a prohibition: it forbids certain things from happening. The more a theory forbids, the better it is. A theory which is not refutable by any conceivable event is non-scientific. Irrefutability is not a virtue of a theory (as people often think) but a vice. Every genuine test of a theory is an attempt to falsify it or to refute it. Testability is falsifiability; but there are degrees of testability: some theories are more testable, more exposed to refutation, than others; they take, as it were, greater risks. Confirming evidence should not count except when it is the result of a genuine test of the theory, and this means that it can be presented as a serious but unsuccessful attempt to falsify the theory. (I now speak in such cases of "corroborating evidence".) Some genuinely testable theories, when


id: scientific-theory-20260505-6
file: data/en.wikipedia.org/wiki/Scientific_theory-6.md
category: reference
title: Scientific theory
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientific_theory
date_saved: 2026-05-05T03:17:41.183216+00:00
instance: kb-cron
parent: scientific-theory-20260505-0
summary:
A theory is something other than myself. It may be set out on paper as a system of rules, and it is the more truly a theory the more completely it can be put down in such terms. Mathematical theory reaches the highest perfection in this respect. But even a geographical map fully embodies in itself a set of strict rules for finding one's way through a region of otherwise uncharted experience. Indeed, all theory may be regarded as a kind of map extended over space and time. A scientific theory can also be thought of as a book that captures the fundamental information about the world, a book that must be researched, written, and shared. In 1623, Galileo Galilei wrote: 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


id: scientism-20260505-0
file: data/en.wikipedia.org/wiki/Scientism-0.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:17:42.382331+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
Scientism is the belief that science and the scientific method are the best or only way to render truth about the world and reality. While the term was defined originally to mean "methods and attitudes typical of or attributed to natural scientists", some scholars, as well as political and religious leaders, have also adopted it as a pejorative term with the meaning "an exaggerated trust in the efficacy of the methods of natural science applied to all areas of investigation (as in philosophy, the social sciences, and the humanities)". == Overview == Francis Bacon has been viewed by some scholars as an early proponent of scientism, but this is a modern assertion as Bacon was a devout Anglican, writing in his Essays, "a little philosophy inclineth man's mind to atheism, but depth in philosophy bringeth men's minds about to religion." With respect to the philosophy of science, the term scientism frequently implies a critique of the more extreme expressions of logical positivism and has been used by social scientists such as Friedrich Hayek, philosophers of science such as Karl Popper, and philosophers such as Mary Midgley, the later Hilary Putnam, and Tzvetan Todorov to describe (for example) the dogmatic endorsement


id: scientism-20260505-1
file: data/en.wikipedia.org/wiki/Scientism-1.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:17:42.382331+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
It is used to criticize a totalizing opinion of science as if it were capable of describing all reality and knowledge, or as if it were the only true method to acquire knowledge about reality and the nature of things; It is used, often pejoratively, to denote violations by which the theories and methods of one (scientific) discipline are applied inappropriately to another (scientific or non-scientific) discipline and its domain. An example of this second usage is to term as scientism any attempt to claim science as the only or primary source of human values (a traditional domain of ethics) or as the source of meaning and purpose (a traditional domain of religion and related worldviews). The term scientism was popularized by F. A. Hayek, who defined it in 1942 as the "slavish imitation of the method and language of Science". Mathematician Alexander Grothendieck, in his 1971 essay "The New Universal Church", characterized scientism as a religion-like ideology that advocates scientific reductionism, scientific authoritarianism, political technocracy and technological salvation, while denying the epistemological validity of feelings and experiences such as love, emotion, beauty and fulfillment. He predicted that "in coming years, the chief political dividing line will fall less and


id: scientism-20260505-2
file: data/en.wikipedia.org/wiki/Scientism-2.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:17:42.382331+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
== Relevance to debates about science and religion == Both religious and non-religious scholars have applied the term scientism to individuals associated with New Atheism. Theologian John Haught argued that philosopher Daniel Dennett and other New Atheists subscribe to a belief system of scientific naturalism, which includes the dogma that "only nature, including humans and our creations, is real: that God does not exist; and that science alone can give us complete and reliable knowledge of reality." Haught argued that this belief system is self-refuting since it requires its adherents to assent to beliefs that violate its own stated requirements for knowledge. Christian philosopher Peter Williams argued in 2013 that it is only by conflating science with scientism that New Atheists feel qualified to "pontificate on metaphysical issues". Daniel Dennett responded to religious criticism of his 2006 book Breaking the Spell: Religion as a Natural Phenomenon by saying that accusations of scientism "[are] an all-purpose, wild-card smear ... When someone puts forward a scientific theory that [religious critics] really don't like, they just try to discredit it as 'scientism'. But when it comes to facts, and explanations of facts, science is the only game in town". Non-religious scholars have also


id: scientism-20260505-3
file: data/en.wikipedia.org/wiki/Scientism-3.md
category: reference
title: Scientism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Scientism
date_saved: 2026-05-05T03:17:42.382331+00:00
instance: kb-cron
parent: scientism-20260505-0
summary:
Thomas M. Lessl argued that religious themes persist in what he terms scientism, the public rhetoric of science. There are two methods of describing this idea of scientism: the epistemological method (the assumption that the scientific method trumps other ways of knowing) and the ontological method (that the rational mind represents the world and both operate in knowable ways). According to Lessl, the ontological method is an attempt to "resolve the conflict between rationalism and skepticism". Lessl also argued that without scientism, there would not be a scientific culture. == Rationalization and modernity == In the introduction to his collected works on the sociology of religion, Max Weber asked why "the scientific, the artistic, the political, or the economic development [elsewhere] ... did not enter upon that path of rationalization which is peculiar to the Occident?" According to the German social theorist Jürgen Habermas, "For Weber, the intrinsic (that is, not merely contingent) relationship between modernity and what he called 'Occidental rationalism' was still self-evident." Weber described a process of rationalisation, disenchantment and the "disintegration of religious world views" that resulted in modern secular societies and capitalism. "Modernization" was introduced as a technical term only in the 1950s. It is


id: secondary-research-20260505-0
file: data/en.wikipedia.org/wiki/Secondary_research-0.md
category: reference
title: Secondary research
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Secondary_research
date_saved: 2026-05-05T03:17:43.696884+00:00
instance: kb-cron
parent: secondary-research-20260505-0
summary:
Secondary research involves the summary, collation and/or synthesis of existing research. Secondary research is contrasted with primary research in that primary research involves the generation of data, whereas secondary research uses primary research sources as a source of data for analysis. A notable marker of primary research is the inclusion of a "methods" section, where the authors describe how the data was generated. Common examples of secondary research include textbooks, encyclopedias, news articles, review articles, and meta analyses. When conducting secondary research, authors may draw data from published academic papers, government documents, statistical databases, and historical records. == Fields == The term is widely used in fields such as history, legal research, market research, and Wikipedia editing. The principal methodology in health secondary research is the systematic review, commonly using meta-analytic statistical techniques. Other methods of synthesis, like realist reviews and meta-narrative reviews, have been developed in the 21st century. Secondary market research includes the reuse by a second party of any data collected from a first party such as telephone interviews or surveys. Secondary market research can be broken up into two categories: information from internal sources such as an agency or company, and information from external sources held


id: selection-bias-20260505-0
file: data/en.wikipedia.org/wiki/Selection_bias-0.md
category: reference
title: Selection bias
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Selection_bias
date_saved: 2026-05-05T03:17:44.818866+00:00
instance: kb-cron
parent: selection-bias-20260505-0
summary:
Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that the association between exposure and outcome among those selected for analysis differs from the association among those eligible. It typically occurs when researchers condition on a factor that is influenced both by the exposure and the outcome (or their causes), creating a false association between them. Selection bias encompasses several forms of bias, including differential loss-to-follow-up, incidence–prevalence bias, volunteer bias, healthy-worker bias, and nonresponse bias. == Types of bias == === Sampling bias === Sampling bias is systematic error due to a non-random sample of a population, causing some members of the population to be less likely to be included than others, resulting in a biased sample, defined as a statistical sample of a population (or non-human factors) in which all participants are not equally balanced or objectively represented. It is mostly classified as a subtype of selection bias, sometimes specifically termed sample selection bias, but some classify it as a separate type of bias. A distinction of sampling bias (albeit not a universally accepted one) is that it undermines the external validity of a test (the ability of


id: selection-bias-20260505-1
file: data/en.wikipedia.org/wiki/Selection_bias-1.md
category: reference
title: Selection bias
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Selection_bias
date_saved: 2026-05-05T03:17:44.818866+00:00
instance: kb-cron
parent: selection-bias-20260505-0
summary:
=== Observer selection === Philosopher Nick Bostrom has argued that data are filtered not only by study design and measurement, but by the necessary precondition that there has to be someone doing a study. In situations where the existence of the observer or the study is correlated with the data, observation selection effects occur, and anthropic reasoning is required. An example is the past impact event record of Earth: if large impacts cause mass extinctions and ecological disruptions precluding the evolution of intelligent observers for long periods, no one will observe any evidence of large impacts in the recent past (since they would have prevented intelligent observers from evolving). Hence there is a potential bias in the impact record of Earth. Astronomical existential risks might similarly be underestimated due to selection bias, and an anthropic correction has to be introduced. === Volunteer bias === Self-selection bias or a volunteer bias in studies offer further threats to the validity of a study as these participants may have intrinsically different characteristics from the target population of the study. Studies have shown that volunteers tend to come from a higher social standing than from a lower socio-economic background. Furthermore, another study shows that


id: self-experimentation-20260505-0
file: data/en.wikipedia.org/wiki/Self-experimentation-0.md
category: reference
title: Self-experimentation
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation
date_saved: 2026-05-05T03:17:49.300856+00:00
instance: kb-cron
parent: self-experimentation-20260505-0
summary:
Self-experimentation refers to single-subject research in which the experimenter conducts the experiment on themself. Usually, this means that a single person is the designer, operator, subject, analyst, and user or reporter of the experiment. Self-experimentation is an example of citizen science since it can be done by patients or people interested in their own health and well-being, as both research subjects and self-experimenters. It is also referred to as personal science or N-of-1 research. == Biology and medicine == Human scientific self-experimentation principally (though not necessarily) falls into the fields of medicine and psychology. Self-experimentation has a long and well-documented history in medicine which continues to the present day. For example, after failed attempts to infect piglets in 1984, Barry Marshall drank a petri dish of Helicobacter pylori from a patient, and soon developed gastritis, achlorhydria, stomach discomfort, nausea, vomiting, and halitosis. The results were published in 1985 in the Medical Journal of Australia, and is among the most cited articles from the journal. He was awarded the Nobel Prize in Physiology or Medicine in 2005. Evaluations have been presented in the context of clinical trials and program evaluations. == Psychology == In psychology, the best-known self-experiments are the memory


id: self-experimentation-in-medicine-20260505-0
file: data/en.wikipedia.org/wiki/Self-experimentation_in_medicine-0.md
category: reference
title: Self-experimentation in medicine
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation_in_medicine
date_saved: 2026-05-05T03:17:50.473562+00:00
instance: kb-cron
parent: self-experimentation-in-medicine-20260505-0
summary:
Self-experimentation refers to scientific experimentation in which the experimenter conducts the experiment on themself. Often this means that the designer, operator, subject, analyst, and user or reporter of the experiment are all the same. Self-experimentation has a long and well-documented history in medicine which continues to the present. Some of these experiments have been very valuable and shed new and often unexpected insights into different areas of medicine. There are many motivations for self-experiment. These include the wish to get results quickly and avoid the need for a formal organisational structure, to take the ethical stance of taking the same risk as volunteers, or just a desire to do good for humanity. Other ethical issues include whether a researcher should self-experiment because another volunteer would not get the same benefit as the researcher will get, and the question of whether informed consent of a volunteer can truly be given by those outside a research program. A number of distinguished scientists have undertaken self-experimentation, including at least five Nobel laureates; in several cases, the prize was awarded for findings the self-experimentation made possible. Many experiments were dangerous; various people exposed themselves to pathogenic, toxic or radioactive materials. Some self-experimenters, like Jesse


id: self-experimentation-in-medicine-20260505-1
file: data/en.wikipedia.org/wiki/Self-experimentation_in_medicine-1.md
category: reference
title: Self-experimentation in medicine
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation_in_medicine
date_saved: 2026-05-05T03:17:50.473562+00:00
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parent: self-experimentation-in-medicine-20260505-0
summary:
== Ethics == As already mentioned, it is an ethical principle that the researcher should not inflict on volunteers anything that the researcher would not be willing to do to themself, but the researcher is not always a suitable, or even possible, subject for the experiment. For instance, the researcher may be the wrong sex if the research is into hormone treatment for women, or may be too old, or too young. The ethical question for the researchers is would they agree to the experiment if they were in the same position as the volunteers? Another issue that can lead researchers not to take part is whether the researcher would stand to gain any benefit from taking part in the experiment. It is an ethical principle that volunteers must stand to gain some benefit from the research, even if that is only a remote future possibility of treatment being found for a disease that they only have a small chance of contracting. Tests on experimental drugs are sometimes conducted on sufferers of an untreatable condition. If the researcher does not have that condition then there can be no possible benefit to them personally. For instance, Ronald C. Desrosiers in responding


id: self-experimentation-in-medicine-20260505-2
file: data/en.wikipedia.org/wiki/Self-experimentation_in_medicine-2.md
category: reference
title: Self-experimentation in medicine
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation_in_medicine
date_saved: 2026-05-05T03:17:50.473562+00:00
instance: kb-cron
parent: self-experimentation-in-medicine-20260505-0
summary:
=== Anaesthesia === Dentist Horace Wells made multiple experiments with nitrous oxide, diethyl ether, and chloroform while trying to determine their uses as anaesthetics. The first, conducted in 1844, consisted of having his assistant John Riggs dose him with nitrous oxide and then extract one of his teeth. His later self-experimentation of ether and chloroform took place in 1848, and he eventually became addicted to chloroform due to excessive use. He inhaled chloroform as an anaesthetic shortly before committing suicide on January 24, 1848. Lidocaine, the first amino amide–type local anaesthetic, was first synthesized under the name xylocaine by Swedish chemist Nils Löfgren in 1943. His colleague Bengt Lundqvist performed the first injection anaesthesia experiments on himself. === Asthma === Roger Altounyan developed the use of sodium cromoglycate as a remedy for asthma, based on khella, a traditional Middle Eastern remedy, with experiments on himself. === Blood === ==== ABO blood group system ==== Dr. Karl Landsteiner's discovery of the ABO blood group system in 1900 was based on an analysis of blood samples from six members of his laboratory staff, including himself. ==== Thrombocytopenia ==== In the Harrington–Hollingsworth experiment in 1950, William J. Harrington performed an exchange blood transfusion


id: self-experimentation-in-medicine-20260505-3
file: data/en.wikipedia.org/wiki/Self-experimentation_in_medicine-3.md
category: reference
title: Self-experimentation in medicine
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation_in_medicine
date_saved: 2026-05-05T03:17:50.473562+00:00
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parent: self-experimentation-in-medicine-20260505-0
summary:
===== Helicobacter pylori ===== In 1984 a Western Australian scientist, Dr Barry Marshall, discovered the link between Helicobacter pylori (at that time known as Campylobacter pylori) and gastritis. This was based on a series of self-experiments that involved gastroscopy and biopsy, ingestion of H. pylori, regastroscopy and biopsy and subsequent treatment with tinidazole. His only option was self-experimentation: ethical measures forbade him from administering H. pylori to any other person. In 2005, Marshall and his long-time collaborator Robin Warren were awarded Nobel Prize in Physiology or Medicine, "for their discovery of the bacterium Helicobacter pylori and its role in gastritis and peptic ulcer disease". Marshall's experiment debunked the long-held belief of the medical profession that stress was the cause of gastritis. This cleared the way for the development of antibiotic treatments for gastritis and peptic ulcers and a new line of research into the likely role of H. pylori in stomach cancer. ===== Campylobacter jejuni ===== Marshall's investigation was preceded by David A. Robinson who, in 1980, ingested Campylobacter jejuni, a bacterium found in cow's milk, to investigate whether gastritis could be caused by drinking milk infected with C. jejuni. Robinson became sick as a result. Robinson needed to do


id: self-experimentation-in-medicine-20260505-4
file: data/en.wikipedia.org/wiki/Self-experimentation_in_medicine-4.md
category: reference
title: Self-experimentation in medicine
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation_in_medicine
date_saved: 2026-05-05T03:17:50.473562+00:00
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parent: self-experimentation-in-medicine-20260505-0
summary:
==== Disulfiram ==== In 1945, during the German occupation of Denmark, Erik Jacobsen and Jens Hald at the Danish drug company Medicinalco (which had a group of enthusiastic self-experimenters that called itself the "Death Battalion") were exploring the possible use of disulfiram to treat intestinal parasites, and in the course of testing it on themselves, accidentally discovered its effects (Disulfiram-alcohol reaction) when alcohol is ingested, which led several years later to the drug called Antabuse. ==== Furan ==== Chauncey D. Leake, in 1930, took furan as a possible substitute for aspirin but it just gave him a splitting headache and painful urination that lasted three days. ==== Grapefruit juice ==== David G. Bailey, in 1989, was researching the effects of drinking alcohol while taking the then experimental drug felodipine. It was usual in this kind of research to mix the alcohol with orange juice but Bailey did not like the taste of this drink so used grapefruit juice instead. Bailey found that there was three times more felodipine in his, and fellow researchers', blood than had been reported by other scientists using orange juice. It was later found that grapefruit juice suppresses an enzyme responsible for breaking down a large


id: self-experimentation-in-medicine-20260505-5
file: data/en.wikipedia.org/wiki/Self-experimentation_in_medicine-5.md
category: reference
title: Self-experimentation in medicine
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation_in_medicine
date_saved: 2026-05-05T03:17:50.473562+00:00
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parent: self-experimentation-in-medicine-20260505-0
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==== Hanging ==== In the early 1900s Nicolae Minovici, a professor of forensic science in Bucharest, undertook a series of experiments into hanging. At first he put the noose around his neck while lying down and had an assistant put tension on the rope. He then moved on to full suspension by the neck. Finally, he attempted suspension with a slipping hangman's knot, but the pain was too great for him to continue. He could not swallow for a month. Minovici was determined to surpass a record set by Dr. Fleichmann of Erlangen, who in 1832, self-asphyxiated for two minutes. However, Minovici could not get close to this and disbelieved Fleichmann. Minovici and Fleichmann are not the only ones to self-experiment with strangulation. Graeme Hammond, a doctor in New York, tried it in 1882. Francis Bacon described an even earlier occasion in 1623 when the self-experimenter stepped off a stool with a rope around his neck, but was unable to regain his footing on the stool without assistance. ==== Rapid acceleration ==== John Paul Stapp, in 1954, sat in a rocket sled fired along rails in a series of steadily more violent tests. Speeds reached 631 mph, almost the speed


id: self-experimentation-in-medicine-20260505-6
file: data/en.wikipedia.org/wiki/Self-experimentation_in_medicine-6.md
category: reference
title: Self-experimentation in medicine
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Self-experimentation_in_medicine
date_saved: 2026-05-05T03:17:50.473562+00:00
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parent: self-experimentation-in-medicine-20260505-0
summary:
There have been several cases of surgeons operating on themselves, but most often it has been in the nature of an emergency rather than experiment. Such a case was Leonid Rogozov who was obliged to remove his own appendix in 1961 while stranded in Antarctica in winter. However, the first surgeon to carry out this self-operation, Evan O'Neill Kane in 1921, did so with an element of experiment. Although Kane's operation was necessary, it was not necessary to do it himself, so that in itself was experimental. More than that, Kane wished to experience the operation under local anaesthetic before trying the procedure on his patients. Kane advocated a reduction in the use of general anaesthetic by surgeons. In 2023, Michael Raduga, a Russian lucid dreaming researcher, performed self-neurosurgery that included trepanation, electrode implantation, and electrical stimulation of the motor cortex. ==== Sensory deprivation ==== John C. Lilly developed the first sensory deprivation tanks and self-experimented them with the intention to study the origin of consciousness and its relation to the brain by creating an environment which isolates an individual from external stimulation. ==== Temperature and pressure ==== Joseph Barcroft, in 1920, spent six days in a sealed glass chamber


id: serendipity-20260505-0
file: data/en.wikipedia.org/wiki/Serendipity-0.md
category: reference
title: Serendipity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Serendipity
date_saved: 2026-05-05T03:17:51.844802+00:00
instance: kb-cron
parent: serendipity-20260505-0
summary:
Serendipity is an unplanned fortunate discovery. The term was coined by Horace Walpole in 1754. The concept is often associated with scientific and technological breakthroughs, where accidental discoveries led to new insights or inventions. Many significant discoveries in history were serendipitous, including penicillin, Post-it notes, Popsicles, and the microwave oven, arising from unforeseen circumstances that were then recognized and capitalized upon. == Definition == Christian Busch views serendipity as "active luck", where chance encounters and human action come together. A missed flight or a casual walk in the park can lead to new friendships, interests, or even career opportunities. While serendipity in popular usage is often understood as a matter of pure chance, scientific discussions emphasize the crucial role of human agency—recognizing, interpreting, and acting upon unexpected opportunities. This interaction between chance and conscious action has been a key theme in areas such as creativity, leadership, innovation, and entrepreneurship. == Etymology == The first noted use of "serendipity" was by Horace Walpole on 28 January 1754. In a letter he wrote to his friend Horace Mann, Walpole explained an unexpected discovery he had made about a painting of Bianca Cappello, which he recently received from Mann as a gift. The


id: serendipity-20260505-1
file: data/en.wikipedia.org/wiki/Serendipity-1.md
category: reference
title: Serendipity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Serendipity
date_saved: 2026-05-05T03:17:51.844802+00:00
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parent: serendipity-20260505-0
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Carbonated water was invented by Joseph Priestley, independently and by accident, in 1767 when he discovered a method of infusing water with carbon dioxide after having suspended a bowl of water above a beer vat at a brewery in Leeds, Yorkshire. He wrote of the "peculiar satisfaction" he found in drinking it, and in 1772 he published a paper entitled Impregnating Water with Fixed Air. Vulcanization was discovered by Charles Goodyear in 1839 when he accidentally dropped rubber mixed with sulfur on a hot frying pan. He noticed that the resulting rubber was stronger and heat-resistant. Corn flakes were invented in 1894 when John Harvey Kellogg unintentionally left a batch of wheat-berry dough out over night. The next day, he decided to figure out what could be done to salvage it, rather than throwing it out. John, Will, and Ella Kellogg then discerned what happened and realized that this process could be reliably recreated through a process known as tempering. Safety glass first originated when French chemist Édouard Bénédictus accidentally dropped a glass flask in 1903 and noticed that it did not shatter like traditional glass. He then sought to refine the material to create a safer form of glass.


id: serendipity-20260505-2
file: data/en.wikipedia.org/wiki/Serendipity-2.md
category: reference
title: Serendipity
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Serendipity
date_saved: 2026-05-05T03:17:51.844802+00:00
instance: kb-cron
parent: serendipity-20260505-0
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== Related terms == Several uncommonly used terms have been derived from the concept and name of serendipity. William Boyd coined the term zemblanity in the late twentieth century to mean somewhat the opposite of serendipity: "making unhappy, unlucky and expected discoveries occurring by design". The derivation is speculative, but believed to be from Nova Zembla, a barren archipelago once the site of Russian nuclear testing. Bahramdipity is derived directly from Bahram Gur as characterized in The Three Princes of Serendip. It describes the suppression of serendipitous discoveries or research results by powerful individuals. In addition, Solomon & Bronstein (2018) further distinguish between perceptual and realised pseudo-serendipity and nemorinity. == See also == Browse Coincidence Felix culpa Insight Lateral thinking Multiple discovery Role of chance in scientific discoveries Serendipaceratops Serendipity Sapphire Side effect Synchronicity == References == == Further reading == Merton, Robert K.; Barber, Elinor (2004). The Travels and Adventures of Serendipity: A Study in Sociological Semantics and the Sociology of Science. Princeton University Press. ISBN 978-0691117546. (Manuscript written 1958). Hannan, Patrick J. (2006). Serendipity, Luck and Wisdom in Research. iUniverse. ISBN 978-0595365517. Roberts, Royston M. (1989). Serendipity: Accidental Discoveries in Science. Wiley. ISBN 978-0471602033. Isabelle Rivoal and Noel


id: solomon-four-group-design-20260505-0
file: data/en.wikipedia.org/wiki/Solomon_four-group_design-0.md
category: reference
title: Solomon four-group design
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Solomon_four-group_design
date_saved: 2026-05-05T03:17:53.099465+00:00
instance: kb-cron
parent: solomon-four-group-design-20260505-0
summary:
The Solomon four-group design is a research method developed by Richard Solomon in 1949. It is sometimes used in social science, psychology and medicine. It can be used if there are concerns that the treatment might be sensitized by the pre-test. In addition of the usual two groups (treatment and control), it has a second pair of groups who do not receive a pre-intervention evaluation. == Structure == The structure of the trial is shown in the table : The first two groups receive the evaluation test before and after the study, as in a normal two-group trial. The second groups receive the evaluation only after the study. The effectiveness of the treatment can be evaluated by comparisons between groups 1 and 3 and between groups 2 and 4.. In addition, the effect of the pre-treatment evaluation can be calculated by comparing the control group who received the pre-treatment evaluation with those who did not (groups 2 and 4). Various statistical treatments for the Solomon four-group design have been put forward, including Stouffer's Z and Monte Carlo. == References ==


id: source-criticism-20260505-0
file: data/en.wikipedia.org/wiki/Source_criticism-0.md
category: reference
title: Source criticism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Source_criticism
date_saved: 2026-05-05T03:17:54.398591+00:00
instance: kb-cron
parent: source-criticism-20260505-0
summary:
Source criticism (or information evaluation) is the process of evaluating an information source, i.e.: a document, a person, a speech, a fingerprint, a photo, an observation, or anything used in order to obtain knowledge. In relation to a given purpose, a given information source may be more or less valid, reliable or relevant. Broadly, "source criticism" is the interdisciplinary study of how information sources are evaluated for given tasks. == Meaning == Problems in translation: The Danish word kildekritik, like the Norwegian word kildekritikk and the Swedish word källkritik, derived from the German Quellenkritik and is closely associated with the German historian Leopold von Ranke (1795–1886). Historian Wolfgang Hardtwig wrote: His [Ranke's] first work Geschichte der romanischen und germanischen Völker von 1494–1514 (History of the Latin and Teutonic Nations from 1494 to 1514) (1824) was a great success. It already showed some of the basic characteristics of his conception of Europe, and was of historiographical importance particularly because Ranke made an exemplary critical analysis of his sources in a separate volume, Zur Kritik neuerer Geschichtsschreiber (On the Critical Methods of Recent Historians). In this work he raised the method of textual criticism used in the late eighteenth century, particularly in


id: source-criticism-20260505-1
file: data/en.wikipedia.org/wiki/Source_criticism-1.md
category: reference
title: Source criticism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Source_criticism
date_saved: 2026-05-05T03:17:54.398591+00:00
instance: kb-cron
parent: source-criticism-20260505-0
summary:
Empiricism evaluates sources by considering the observations (or sensations) on which they are based. Sources without basis in experience are not seen as valid. Rationalism provides low priority to sources based on observations. In order to be meaningful, observations must be explained by clear ideas or concepts. It is the logical structure and the well definedness that is in focus in evaluating information sources from the rationalist point of view. Historicism evaluates information sources on the basis of their reflection of their sociocultural context and their theoretical development. Pragmatism evaluate sources on the basis of how their values and usefulness to accomplish certain outcomes. Pragmatism is skeptical about claimed neutral information sources. The evaluation of knowledge or information sources cannot be more certain than is the construction of knowledge. If one accepts the principle of fallibilism then one also has to accept that source criticism can never 100% verify knowledge claims. As discussed in the next section, source criticism is intimately linked to scientific methods. The presence of fallacies of argument in sources is another kind of philosophical criterion for evaluating sources. Fallacies are presented by Walton (1998). Among the fallacies are the ad hominem fallacy (the use of personal


id: source-criticism-20260505-2
file: data/en.wikipedia.org/wiki/Source_criticism-2.md
category: reference
title: Source criticism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Source_criticism
date_saved: 2026-05-05T03:17:54.398591+00:00
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parent: source-criticism-20260505-0
summary:
Photos are often manipulated during wars and for political purposes. One well known example is Joseph Stalin's manipulation of a photograph from May 5, 1920, on which Stalin's predecessor Lenin held a speech for Soviet troops that Leon Trotsky attended. Stalin had later Trotsky retouched out of this photograph. (cf. King, 1997). A recent example is reported by Healy (2008) about North Korean leader Kim Jong Il. === Internet sources === Much interest in evaluating Internet sources (such as Wikipedia) is reflected in the scholarly literature of library and information science and in other fields. Mintz (2002) is an edited volume about this issue. Examples of literature examining Internet sources include Chesney (2006), Fritch & Cromwell (2001), Leth & Thurén (2000) and Wilkinson, Bennett, & Oliver (1997). === Archaeology and history === "In history, the term historical method was first introduced in a systematic way in the sixteenth century by Jean Bodin in his treatise of source criticism, Methodus ad facilem historiarium cognitionem (1566). Characteristically, Bodin's treatise intended to establish the ways by which reliable knowledge of the past could be established by checking sources against one another and by so assessing the reliability of the information conveyed by them,


id: source-criticism-20260505-3
file: data/en.wikipedia.org/wiki/Source_criticism-3.md
category: reference
title: Source criticism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Source_criticism
date_saved: 2026-05-05T03:17:54.398591+00:00
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parent: source-criticism-20260505-0
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The most important legal sources are created by parliaments, governments, courts, and legal researchers. They may be written or informal and based on established practices. Views concerning the quality of sources differ among legal philosophies: Legal positivism is the view that the text of the law should be considered in isolation, while legal realism, interpretivism (legal), critical legal studies and feminist legal criticism interprets the law on a broader cultural basis. == See also == == Notes == == References == American Library Association (1994) Evaluating Information: A Basic Checklist. Brochure. American Library Association Anderson, Richard C. (1978). Schema-directed processes in language comprehension. IN: NATO International Conference on Cognitive Psychology and Instruction, 1977, Amsterdam: Cognitive Psychology and Instruction. Ed. by A. M. Lesgold, J. W. Pellegrino, S. D. Fokkema & R. Glaser. New York: Plenum Press (pp. 67–82). Anderson, Richard C. & Pichert, J. W. (1977). Recall of previously unrecallable information following a shift of perspective. Urbana, Il: University of Illinois, Center for the Study of Reading, April. 1977. (Technical Report 41). Available in full-text from: http://eric.ed.gov/ERICDocs/data/ericdocs2sql/content_storage_01/0000019b/80/31/83/58.pdf Bazerman, Charles (1995). The Informed Writer: Using Sources in the Disciplines. 5th ed. Houghton Mifflin. Bee, Ronald E. (1983). Statistics and Source Criticism.


id: source-criticism-20260505-4
file: data/en.wikipedia.org/wiki/Source_criticism-4.md
category: reference
title: Source criticism
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Source_criticism
date_saved: 2026-05-05T03:17:54.398591+00:00
instance: kb-cron
parent: source-criticism-20260505-0
summary:
== External links == The Source Compass: Source Criticism The History Sourcebook: The Need for Source Criticism


id: statistical-alchemy-20260505-0
file: data/en.wikipedia.org/wiki/Statistical_alchemy-0.md
category: reference
title: Statistical alchemy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Statistical_alchemy
date_saved: 2026-05-05T03:17:55.564146+00:00
instance: kb-cron
parent: statistical-alchemy-20260505-0
summary:
Statistical alchemy was a term originated by John Maynard Keynes to describe econometrics in 1939. The phrase has subsequently been used by Alvan Feinstein to describe meta-analysis. It is generally regarded as a deprecatory term which undermines attempts to present such activities as meeting the rigorous standards of science. == Econometrics == Keynes (1939) wrote a review of Jan Tinbergen's Statistical Testing of Business-Cycle Theories. Although he praised Tinbergen for his objectivity, he however depicted his methodology as "black magic" which he regarded as essentially untrustworthy. He was unpersuaded that "this brand of statistical alchemy is ripe to become a branch of science" (emphasis in the original). Often this metaphor is seen as a way of suggesting that econometricians were following a foolhardy pursuit comparable to the alchemical quest of turning base metal into gold. However G. M. P. Swann points out that Keynes was well aware that such eminent early scientists as Isaac Newton. He rather proposes a more nuanced interpretation of the metaphor as referring to the Alkahest, a universal solvent, which, it was claimed could turn stone into water. He claimed that by restricting econometrics to theory, mathematics and statistics, econometricians had discarded other important applied techniques.


id: statistical-inference-20260505-0
file: data/en.wikipedia.org/wiki/Statistical_inference-0.md
category: reference
title: Statistical inference
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Statistical_inference
date_saved: 2026-05-05T03:17:56.828887+00:00
instance: kb-cron
parent: statistical-inference-20260505-0
summary:
Statistical inference is the process of using data analysis to infer properties of an underlying probability distribution. Inferential statistical analysis infers properties of a population, for example by testing hypotheses and deriving estimates. It is assumed that the observed data set is sampled from a larger population. Inferential statistics can be contrasted with descriptive statistics. Descriptive statistics is solely concerned with properties of the observed data, and it does not rest on the assumption that the data come from a larger population. In machine learning, the term inference is sometimes used instead to mean "make a prediction, by evaluating an already trained model"; in this context inferring properties of the model is referred to as training or learning (rather than inference), and using a model for prediction is referred to as inference (instead of prediction); see also predictive inference. == Introduction == Statistical inference makes propositions about a population, using data drawn from the population with some form of sampling. Given a hypothesis about a population, for which we wish to draw inferences, statistical inference consists of (first) selecting a statistical model of the process that generates the data and (second) deducing propositions from the model. Konishi and Kitagawa state


id: statistical-inference-20260505-1
file: data/en.wikipedia.org/wiki/Statistical_inference-1.md
category: reference
title: Statistical inference
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Statistical_inference
date_saved: 2026-05-05T03:17:56.828887+00:00
instance: kb-cron
parent: statistical-inference-20260505-0
summary:
Given the difficulty in specifying exact distributions of sample statistics, many methods have been developed for approximating these. With finite samples, approximation results measure how close a limiting distribution approaches the statistic's sample distribution: For example, with 10,000 independent samples the normal distribution approximates (to two digits of accuracy) the distribution of the sample mean for many population distributions, by the Berry–Esseen theorem. Yet for many practical purposes, the normal approximation provides a good approximation to the sample-mean's distribution when there are 10 (or more) independent samples, according to simulation studies and statisticians' experience. Following Kolmogorov's work in the 1950s, advanced statistics uses approximation theory and functional analysis to quantify the error of approximation. In this approach, the metric geometry of probability distributions is studied; this approach quantifies approximation error with, for example, the Kullback–Leibler divergence, Bregman divergence, and the Hellinger distance. With indefinitely large samples, limiting results like the central limit theorem describe the sample statistic's limiting distribution if one exists. Limiting results are not statements about finite samples, and indeed are irrelevant to finite samples. However, the asymptotic theory of limiting distributions is often invoked for work with finite samples. For example, limiting results are often invoked to


id: statistical-inference-20260505-2
file: data/en.wikipedia.org/wiki/Statistical_inference-2.md
category: reference
title: Statistical inference
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Statistical_inference
date_saved: 2026-05-05T03:17:56.828887+00:00
instance: kb-cron
parent: statistical-inference-20260505-0
summary:
This paradigm calibrates the plausibility of propositions by considering (notional) repeated sampling of a population distribution to produce datasets similar to the one at hand. By considering the dataset's characteristics under repeated sampling, the frequentist properties of a statistical proposition can be quantified—although in practice this quantification may be challenging. ==== Examples of frequentist inference ==== p-value Confidence interval Null hypothesis significance testing ==== Frequentist inference, objectivity, and decision theory ==== One interpretation of frequentist inference (or classical inference) is that it is applicable only in terms of frequency probability; that is, in terms of repeated sampling from a population. However, the approach of Neyman develops these procedures in terms of pre-experiment probabilities. That is, before undertaking an experiment, one decides on a rule for coming to a conclusion such that the probability of being correct is controlled in a suitable way: such a probability need not have a frequentist or repeated sampling interpretation. In contrast, Bayesian inference works in terms of conditional probabilities (i.e. probabilities conditional on the observed data), compared to the marginal (but conditioned on unknown parameters) probabilities used in the frequentist approach. The frequentist procedures of significance testing and confidence intervals can be constructed without regard


id: statistical-inference-20260505-3
file: data/en.wikipedia.org/wiki/Statistical_inference-3.md
category: reference
title: Statistical inference
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Statistical_inference
date_saved: 2026-05-05T03:17:56.828887+00:00
instance: kb-cron
parent: statistical-inference-20260505-0
summary:
Formulating the statistical model: A statistical model is defined based on the problem at hand, specifying the distributional assumptions and the relationship between the observed data and the unknown parameters. The model can be simple, such as a normal distribution with known variance, or complex, such as a hierarchical model with multiple levels of random effects. Constructing the likelihood function: Given the statistical model, the likelihood function is constructed by evaluating the joint probability density or mass function of the observed data as a function of the unknown parameters. This function represents the probability of observing the data for different values of the parameters. Maximizing the likelihood function: The next step is to find the set of parameter values that maximizes the likelihood function. This can be achieved using optimization techniques such as numerical optimization algorithms. The estimated parameter values, often denoted as y ¯ {\displaystyle {\bar {y}}} , are the maximum likelihood estimates (MLEs). Assessing uncertainty: Once the MLEs are obtained, it is crucial to quantify the uncertainty associated with the parameter estimates. This can be done by calculating standard errors, confidence intervals, or conducting hypothesis tests based on asymptotic theory or simulation techniques such as bootstrapping. Model checking:


id: stigler-s-law-of-eponymy-20260505-0
file: data/en.wikipedia.org/wiki/Stigler's_law_of_eponymy-0.md
category: reference
title: Stigler's law of eponymy
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Stigler's_law_of_eponymy
date_saved: 2026-05-05T03:17:58.015991+00:00
instance: kb-cron
parent: stigler-s-law-of-eponymy-20260505-0
summary:
Stigler's law of eponymy, proposed by University of Chicago statistics professor Stephen Stigler in 1980, states that no scientific discovery is named after its original discoverer. Examples include Hubble's law, which was derived by Georges Lemaître two years before Edwin Hubble; the Pythagorean theorem, which was known to Babylonian mathematicians and to Indian mathematicians before Pythagoras; and Halley's Comet, which was observed by astronomers since at least 240 BC (although its official designation is due to the first ever mathematical prediction of such astronomical phenomenon in the sky, not to its discovery). Stigler attributed the discovery of Stigler's law to sociologist Robert K. Merton, making "Stigler's law" an example of Stigler's law. In his paper, Stigler wrote: I have chosen as a title for this paper, and for the thesis I wish to present and discuss, "Stigler's law of eponymy". At first glance this may appear to be a flagrant violation of the "Institutional Norm of Humility," and since statisticians are even more aware of the importance of norms than are members of other disciplines, I hasten to add a humble disclaimer. If there is an idea in this paper that is not at least implicit in Merton's The Sociology


id: list-of-examples-of-stigler-s-law-20260505-0
file: data/en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law-0.md
category: reference
title: List of examples of Stigler's law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law
date_saved: 2026-05-05T03:17:59.384401+00:00
instance: kb-cron
parent: list-of-examples-of-stigler-s-law-20260505-0
summary:
Stigler's law concerns the supposed tendency of eponymous expressions for scientific discoveries to honor people other than their respective originators. Examples include: == A == Aharonov–Bohm effect. Werner Ehrenberg and Raymond E. Siday first predicted the effect in 1949, and similar effects were later rediscovered by Yakir Aharonov and David Bohm in 1959. Ampère's circuital law was inspired by the experimental results of André-Marie Ampère, and named in his honor. However, it was James Clerk Maxwell who combined those results into a single mathematical law. Arabic numerals, first developed in India around 7th century. Archimedes' screw is known to predate Archimedes by at least three centuries in ancient Babylon. Argand diagram by Caspar Wessel in 1797, predating Jean-Robert Argand by nine years. Arrhenius equation. The equation was first proposed by the Dutch chemist J. H. van 't Hoff in 1884; five years later in 1889, the Swedish chemist Svante Arrhenius provided a physical justification and interpretation for it. Auger effect. First discovered by Lise Meitner in 1922 and then, independently, in 1923 by Pierre Victor Auger. == B == Bailey–Borwein–Plouffe formula was discovered by Simon Plouffe, who has since expressed regret at having to share credit for his discovery. Bell


id: list-of-examples-of-stigler-s-law-20260505-1
file: data/en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law-1.md
category: reference
title: List of examples of Stigler's law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law
date_saved: 2026-05-05T03:17:59.384401+00:00
instance: kb-cron
parent: list-of-examples-of-stigler-s-law-20260505-0
summary:
== C == Cantor–Bernstein–Schröder theorem (also known by other variations, such as Schröder-Bernstein theorem) first proved by Richard Dedekind Cantor set, discovered in 1874 by Henry John Stephen Smith and introduced by German mathematician Georg Cantor 1883. Carmichael number: Václav Šimerka listed the first seven Carmichael numbers in 1885; they are named after Robert Daniel Carmichael who subsequently discovered the first one in 1910. Cartan matrices, first investigated by Wilhelm Killing. Cardano's formula, the solution to general cubic equations. Cardano stated that it was discovered by Scipione del Ferro, who passed the knowledge to his student Antonio Maria Fior. Around 1535 Niccolò Fontana Tartaglia learned of this from Fior and re-derived the formula for the cubic, which he later shared with Cardano. Cassegrain reflector, named after a design published in 1672 which has been attributed to Laurent Cassegrain, but was already known to Bonaventura Cavalieri in 1632 and Marin Mersenne in 1636. Cartesian duality: Named for René Descartes, but Teresa of Avila and her contemporaries wrote about similar methods of philosophical exploration eight to ten years before Descartes was born. Cavendish balance for measuring the universal gravitational constant, first devised and constructed by John Michell. The Cayley–Hamilton theorem was proven


id: list-of-examples-of-stigler-s-law-20260505-2
file: data/en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law-2.md
category: reference
title: List of examples of Stigler's law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law
date_saved: 2026-05-05T03:17:59.384401+00:00
instance: kb-cron
parent: list-of-examples-of-stigler-s-law-20260505-0
summary:
== G == Galileo's paradox: the property of infinite sets was known to Duns Scotus. Gauss's law: first described by Joseph Louis Lagrange in 1773, over half a century before Gauss. Gauss's theorem: first proved by Ostrogradsky in 1831. Gaussian distribution: the normal distribution was introduced by Abraham de Moivre in 1733, but named after Carl Friedrich Gauss who began using it in 1794. Gaussian elimination: was already in well-known textbooks such as Thomas Simpson's when Gauss in 1809 remarked that he used "common elimination." Gibbs phenomenon: named for Josiah Willard Gibbs who published in 1901. First discovered by Henry Wilbraham in 1851. Goodhart's law, with several earlier variations, like Campbell's law. The Graetz circuit, also known as the diode bridge, was invented and patented in 1896 by Karol Pollak a year before it was published by Leo Graetz. The Graham escapement is often erroneously credited to English clockmaker George Graham but it was actually invented by astronomer Richard Towneley. The Gregorian telescope is named after James Gregory, who published it in 1663, but was already known to Bonaventura Cavalieri in 1632 and Marin Mersenne in 1636. Gresham's law was described by Nicolaus Copernicus in 1519, the year of Thomas


id: list-of-examples-of-stigler-s-law-20260505-3
file: data/en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law-3.md
category: reference
title: List of examples of Stigler's law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law
date_saved: 2026-05-05T03:17:59.384401+00:00
instance: kb-cron
parent: list-of-examples-of-stigler-s-law-20260505-0
summary:
== M == Maxwell's equations. The modern form of the equations in their most common formulation is credited to Oliver Heaviside, based on James Clerk Maxwell's original work. Madelung rule, describing the order in which electron orbitals are filled, named after Erwin Madelung but first discovered by Charles Janet. Magellanic Clouds, while observed by Antonio Pigafetta on one of Magellan's voyages there were previous reports made by 16th century Italian authors Peter Martyr d'Anghiera and Andrea Corsali and earlier reports by Arabic astronomers. Matthew effect, named by Robert K. Merton after the writer of the Gospel of Matthew quoting the words of Jesus. Meadow's law, the formulation that one cot death in a family is tragic, two suspicious, and three murder, originally described by D.J. and V.J.M. Di Maio. Metropolis–Hastings algorithm. The algorithm was named after Nicholas Metropolis, who was the director of the Theoretical Division of Los Alamos National Laboratory at the time of writing the paper Equation of State Calculations by Fast Computing Machines. However, Metropolis did not contribute to that study in any way, as confirmed by various sources. The research problem was proposed by Augusta H. Teller and solved by Marshall N. Rosenbluth and Arianna W.


id: list-of-examples-of-stigler-s-law-20260505-4
file: data/en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law-4.md
category: reference
title: List of examples of Stigler's law
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/List_of_examples_of_Stigler's_law
date_saved: 2026-05-05T03:17:59.384401+00:00
instance: kb-cron
parent: list-of-examples-of-stigler-s-law-20260505-0
summary:
== R == The Reynolds number in fluid mechanics was introduced by George Stokes, but is named after Osborne Reynolds, who popularized its use. Richards equation is attributed to Richards in his 1931 publication, but was earlier introduced by Richardson in 1922 in his book "Weather prediction by numerical process." (Cambridge University press. p. 262) as pointed out by John Knight and Peter Raats in "The contributions of Lewis Fry Richardson to drainage theory, soil physics, and the soil-plant-atmosphere continuum" EGU General Assembly 2016. Russell's paradox is a paradox in set theory that Bertrand Russell discovered and published in 1901. However, Ernst Zermelo had independently discovered the paradox in 1899. == S == The Sankey diagram was invented by Charles Joseph Minard The Schottky diode was neither discovered by Schottky nor its operation correctly explained by him. The actual nature of the metal–semiconductor junction was noted by Hans Bethe. The Schröder–Bernstein theorem in set theory was first stated without proof by Georg Cantor and first proved by Richard Dedekind Shuey's equation from 1985, which is an approximation of the Zoeprittz Equation first published in 1919. Simpson's paradox, a term introduced by Colin R. Blyth in 1972; but Edward Simpson did


id: strong-inference-20260505-0
file: data/en.wikipedia.org/wiki/Strong_inference-0.md
category: reference
title: Strong inference
tags: science, encyclopedia
source_url: https://en.wikipedia.org/wiki/Strong_inference
date_saved: 2026-05-05T03:18:00.515209+00:00
instance: kb-cron
parent: strong-inference-20260505-0
summary:
In philosophy of science, strong inference is a model of scientific inquiry that emphasizes the need for alternative hypotheses, rather than a single hypothesis to avoid confirmation bias. The term "strong inference" was coined by John R. Platt, a biophysicist at the University of Chicago. Platt notes that some fields, such as molecular biology and high-energy physics, seem to adhere strongly to strong inference, with very beneficial results for the rate of progress in those fields. == The single hypothesis problem == The problem with single hypotheses, confirmation bias, was aptly described by Thomas Chrowder Chamberlin in 1897: The moment one has offered an original explanation for a phenomenon which seems satisfactory, that moment affection for [one’s] intellectual child springs into existence, and as the explanation grows into a definite theory [one’s] parental affections cluster about [the] offspring and it grows more and more dear .... There springs up also unwittingly a pressing of the theory to make it fit the facts and a pressing of the facts to make them fit the theory... The temptation to misinterpret results that contradict the desired hypothesis is probably irresistible. Despite the admonitions of Platt, reviewers of grant-applications often require "A Hypothesis" as


