Scientific modelling in the context of Understanding

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:

Paranormal events are purported phenomena described in popular culture, folklore, and other non-scientific bodies of knowledge, whose existence within these contexts is described as being beyond the scope of normal scientific understanding. Notable paranormal beliefs include those that pertain to extrasensory perceptions (for example, telepathy), and the pseudosciences of ghost hunting, cryptozoology, and ufology.

Proposals regarding the paranormal are different from scientific hypotheses or speculations extrapolated from scientific evidence because scientific ideas are grounded in empirical observations and experimental data gained through the scientific method. In contrast, those who argue for the existence of the paranormal explicitly do not base their arguments on empirical evidence but rather on anecdote, testimony and suspicion. The standard scientific models give the explanation that what appears to be paranormal phenomena is usually a misinterpretation, misunderstanding or anomalous variation of natural phenomena.

A simulation is an imitative representation of a process or system that could exist in the real world. In this broad sense, simulation can often be used interchangeably with model. Sometimes a clear distinction between the two terms is made, in which simulations require the use of models; the model represents the key characteristics or behaviors of the selected system or process, whereas the simulation represents the evolution of the model over time. Another way to distinguish between the terms is to define simulation as experimentation with the help of a model. This definition includes time-independent simulations. Often, computers are used to execute the simulation.

Simulation is used in many contexts, such as simulation of technology for performance tuning or optimizing, safety engineering, testing, training, education, and video games. Simulation is also used with scientific modelling of natural systems or human systems to gain insight into their functioning, as in economics. Simulation can be used to show the eventual real effects of alternative conditions and courses of action. Simulation is also used when the real system cannot be engaged, because it may not be accessible, or it may be dangerous or unacceptable to engage, or it is being designed but not yet built, or it may simply not exist.

Generative grammar is a research tradition in linguistics that aims to explain the cognitive basis of language by formulating and testing explicit models of humans' subconscious grammatical knowledge. Generative linguists tend to share certain working assumptions such as the competence–performance distinction and the notion that some domain-specific aspects of grammar are partly innate in humans. These assumptions are often rejected in non-generative approaches such as usage-based models of language. Generative linguistics includes work in core areas such as syntax, semantics, phonology, psycholinguistics, and language acquisition, with additional extensions to topics including biolinguistics and music cognition.

Generative grammar began in the late 1950s with the work of Noam Chomsky, having roots in earlier approaches such as structural linguistics. The earliest version of Chomsky's model was called Transformational grammar, with subsequent iterations known as Government and binding theory and the Minimalist program. Other present-day generative models include Optimality theory, Categorial grammar, and Tree-adjoining grammar.

Ornithology, from Ancient Greek ὄρνις (órnis), meaning "bird", and λόγος (lógos), meaning "study", is a branch of zoology dedicated to the study of birds. Several aspects of ornithology differ from related disciplines, due partly to the high visibility and the aesthetic appeal of birds. It has also been an area with a large contribution made by amateurs in terms of time, resources, and financial support. Studies on birds have helped develop key concepts in biology including evolution, behaviour and ecology such as the definition of species, the process of speciation, instinct, learning, ecological niches, guilds, insular biogeography, phylogeography, and conservation.

While early ornithology was principally concerned with descriptions and distributions of species, ornithologists today seek answers to very specific questions, often using birds as models to test hypotheses or predictions based on theories. Most modern biological theories apply across life forms, and the number of scientists who identify themselves as "ornithologists" has therefore declined. A wide range of tools and techniques are used in ornithology, both inside the laboratory and out in the field, and innovations are constantly made. Most biologists who recognise themselves as "ornithologists" study specific biology research areas, such as anatomy, physiology, taxonomy (phylogenetics), ecology, or behaviour.

An analog computer or analogue computer is a type of computation machine (computer) that uses physical phenomena such as electrical, mechanical, or hydraulic quantities behaving according to the mathematical principles in question (analog signals) to model the problem being solved. In contrast, digital computers represent varying quantities symbolically and by discrete values of both time and amplitude (digital signals).

Analog computers can have a very wide range of complexity. Slide rules and nomograms are the simplest, while naval gunfire control computers and large hybrid digital/analog computers were among the most complicated. Complex mechanisms for process control and protective relays used analog computation to perform control and protective functions. The common property of all of them is that they don't use algorithms to determine the fashion of how the computer works. They rather use a structure analogous to the system to be solved (a so called analogon, model or analogy) which is also eponymous to the term analog computer, because they represent a model.

Scientific racism, sometimes termed biological racism, is the pseudoscientific belief that the human species is divided into biologically distinct taxa called "races", and that empirical evidence exists to support or justify racial discrimination, racial inferiority, or racial superiority. Before the mid-20th century, scientific racism was accepted throughout the scientific community, but it is no longer considered scientific. The division of humankind into biologically separate groups, along with the assignment of particular physical and mental characteristics to these groups through constructing and applying corresponding explanatory models, is referred to as racialism, racial realism, race realism, or race science by those who support these ideas. Modern scientific consensus rejects this view as being irreconcilable with modern genetic research.

Scientific racism misapplies, misconstrues, or distorts anthropology (notably physical anthropology), craniometry, evolutionary biology, and other disciplines or pseudo-disciplines through proposing anthropological typologies to classify human populations into physically discrete human races, some of which may be asserted to be superior or inferior to others.

In philosophy of science, idealization is the process by which scientific models assume facts about the phenomenon being modeled that are strictly false but make models easier to understand or solve. That is, it is determined whether the phenomenon approximates an "ideal case," then the model is applied to make a prediction based on that ideal case.

If an approximation is accurate, the model will have high predictive power; for example, it is not usually necessary to account for air resistance when determining the acceleration of a falling bowling ball, and doing so would be more complicated. In this case, air resistance is idealized to be zero. Although this is not strictly true, it is a good approximation because its effect is negligible compared to that of gravity.

The multiregional hypothesis, multiregional evolution (MRE), or polycentric hypothesis, is a scientific model that provides an alternative explanation to the more widely accepted "Out of Africa" model of monogenesis for the pattern of human evolution.

Multiregional evolution holds that the human species first arose around two million years ago and subsequent human evolution has been within a single, continuous human species. This species encompasses all archaic human forms such as Homo erectus, Denisovans, and Neanderthals as well as modern forms, and evolved worldwide to the diverse populations of anatomically modern humans (Homo sapiens).

Experimental data in science and engineering is data produced by a measurement, test method, experimental design or quasi-experimental design. In clinical research any data produced are the result of a clinical trial. Experimental data may be qualitative or quantitative, each being appropriate for different investigations.

Generally speaking, qualitative data are considered more descriptive and can be subjective in comparison to having a continuous measurement scale that produces numbers. Whereas quantitative data are gathered in a manner that is normally experimentally repeatable, qualitative information is usually more closely related to phenomenal meaning and is, therefore, subject to interpretation by individual observers.

Implementation is the realization of an application, execution of a plan, idea, model, design, specification, standard, algorithm, policy, or the administration or management of a process or objective.

In linguistics, transformational grammar (TG) or transformational-generative grammar (TGG) was the earliest model of grammar proposed within the research tradition of generative grammar. Like current generative theories, it treated grammar as a system of formal rules that generate all and only grammatical sentences of a given language. What was distinctive about transformational grammar was that it posited transformation rules that mapped a sentence's deep structure to its pronounced form. For example, in many variants of transformational grammar, the English active voice sentence "Emma saw Daisy" and its passive counterpart "Daisy was seen by Emma" share a common deep structure generated by phrase structure rules, differing only in that the latter's structure is modified by a passivization transformation rule.

Coalescent theory is a model of how alleles sampled from a population may have originated from a common ancestor. In the simplest case, coalescent theory assumes no recombination, no natural selection, and no gene flow or population structure, meaning that each variant is equally likely to have been passed from one generation to the next. The model looks backward in time, merging alleles into a single ancestral copy according to a random process in coalescence events. Under this model, the expected time between successive coalescence events increases almost exponentially back in time (with wide variance). Variance in the model comes from both the random passing of alleles from one generation to the next, and the random occurrence of mutations in these alleles.

The mathematical theory of the coalescent was developed independently by several groups in the early 1980s as a natural extension of classical population genetics theory and models, but can be primarily attributed to John Kingman. Advances in coalescent theory include recombination, selection, overlapping generations and virtually any arbitrarily complex evolutionary or demographic model in population genetic analysis.

The geographic cycle, or cycle of erosion, is an idealized model that explains the development of relief in landscapes. The model starts with the erosion that follows uplift of land above a base level and ends, if conditions allow, in the formation of a peneplain. Landscapes that show evidence of more than one cycle of erosion are termed "polycyclical". The cycle of erosion and some of its associated concepts have, despite their popularity, been a subject of much criticism.