Scientific modelling
Scientific modeling is a vital process in the scientific method that simplifies complex information through the creation of conceptual or observable models. These models serve to approximate empirical data and can be found in varied forms, including recipes, road maps, and even budget plans, showcasing the pervasive nature of scientific thought beyond traditional science. Models can represent tangible objects, like scale models of airplanes or globes, as well as abstract concepts such as theories and mathematical equations.
Different types of models exist, with physical models providing demonstrative representations, while abstract models engage theoretical ideas. Notable examples include the double helix model of DNA and the food pyramid, which condenses extensive research into accessible formats. Scientific models act as proxies for the subjects they represent, aiding in understanding phenomena that may be impractical to observe directly. By clarifying and conveying complex information, models play a crucial role across various disciplines, helping to communicate scientific outcomes effectively.
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Scientific modelling
Scientific modelling is the process of making complicated information easier to understand through the use of conceptual or observable models. Scientific models are the most basic element of the scientific method and are used to approximate empirical data. Models can be found practically anywhere. Recipes, road maps, history exams, and state budgets are all examples of models. Though these models do not appear related to science, they were created through the use of scientific thought. The process behind scientific modelling is used in many fields including architecture, advertising, finance, and law. Scientific models are an important part of many scientific fields of study.
Models can represent a specific physical object, such as a toy airplane or a globe model of Earth. They can also interpret more abstract notions such as philosophical and biological theories. Scientific models are often used to describe the outcome of an experiment that is not feasible or too large in scope to carry out fully. Therefore, scientific modelling only offers a general breakdown of empirical data or evidence as accurately as possible. Many scientific disciplines use modelling to express concrete and abstract information. A few examples of model expressions include sketches, graphs, diagrams, mathematical equations, and scale models.
Types of Models
Many types of scientific models are used to help interpret complex information. Physical models represent scientific observations that are purely demonstrative. An example of a physical model is a scale model, which is used to either enlarge or shrink an object to make it observable. A globe is a shrunken model of Earth, which allows people to better understand the structure and components of the planet. A plastic model of a snowflake is many times bigger than an actual snowflake and allows viewers to observe the shape and texture of the tiny ice crystal. Many children's toys are also physical models of larger objects, such as airplanes, trucks, and cars. Study models built to resemble the intricacies of human organs or skeletal systems are also considered physical models.
Most scientific models are not tangible, however; instead, they are abstract models. This means they have no physical form. Abstract models involve theoretical ideas and concepts. Examples include predictions, theories, hypotheses, mathematical models, and computer models. The big bang model of the universe is a scientific model that takes no physical form but is understood through visualization. A material model of the big bang with its many phases and formations is not feasible, but a visual representation can be utilized to make the theory more comprehensible. Bohr's model of the atom is another example of an abstract model. Bohr's model describes the minute components of an atom, making it easier for people to visualize the atom, its nucleus, and the protons and neutrons within the nucleus without physically seeing or touching the atom. The food pyramid is an abstract model in the sense that a great deal of multifaceted information is compacted into a small diagram that makes helpful health suggestions.
Function of Models
Models act as stand-ins for the object of study. Scientists have created models for many different contexts, such as the double helix model of DNA. The United States Department of Agriculture (USDA) food pyramid is also a well-known scientific model. The food pyramid recommends how much of each category of food should be ingested to achieve optimum health. This information is a simplification of thousands of studies done over the course of many years relating the consumption of specific foods to health. The food pyramid is a substitute for all of this collected data. Without it, consumers would have to search through the many studies to come to the same conclusion the food pyramid presents. Another example of the stand-in scientific modelling function is the use of rats in scientific experiments. In most studies, the rats are a substitute for humans, who benefit from the data collected from experiments into areas such as cancer and stem cell research. Some scientific models do nothing more than put an otherwise unobservable object on display. Models such as toy models and study models demonstrate nothing more than a basic understanding of what a mechanism looks like.
Most scientific modelling aims to instruct users about a scientific outcome. Scientific models are constructed from data and theories, but it is important to distinguish models from their components. Models can function independently from the theories they complement. Theories offer no concrete accounts of what they propose, whereas models embody specific situations proposed by theories. Models also provide results where theories do not. For example, the big bang model produces perceptible results derived from the big bang theory, which is much more complicated than the model detailing it.
Bibliography
Bailer-Jones, Daniela M. Scientific Models in Philosophy of Science. Pittsburgh: University of Pittsburgh Press, 2009: 1-14. Print. Available at https://books.google.com/books?id=avur50J7UecC&pg=PA222&dq=scientific+modelling&hl=en&sa=X&ei=-2ihVKWGFoS-ggS‗2IHgCQ&ved=0CDAQ6AEwAw#v=onepage&q&f=false
Frigg, Roman, and Stephan Hartmann. "Models in Science." Stanford Encyclopedia of Philosophy. Stanford University. Web. 29 Dec. 2014. http://plato.stanford.edu/entries/models-science/#ModIndThe
Haig, Brian D. "Models." Encyclopedia of Research Design. Ed. Neil J. Salkind. Vol. 2. Thousand Oaks, CA: SAGE Reference, 2010. 826-830. Gale Virtual Reference Library. Web. 29 Dec. 2014. http://go.galegroup.com/ps/retrieve.do?sgHitCountType=None&sort=RELEVANCE&inPS=true&prodId=GVRL&userGroupName=itsbtrial&tabID=T003&searchId=R3&resultListType=RESULT‗LIST&contentSegment=&searchType=BasicSearchForm¤tPosition=3&contentSet=GALE%7CCX1959400257&&docId=GALE|CX1959400257&docType=GALE
Pease, Craig M., and James J. Bull. "Chapter 4. Models are the Building Blocks of Science." University of Texas. The University of Texas at Austin. Web. 29 Dec. 2014. https://www.utexas.edu/courses/bio301d/Topics/Models/Text.html
Wallace, William A., and Kenneth R. Fleischmann. "Models and Modeling." Encyclopedia of Science, Technology, and Ethics. Ed. Carl Mitcham. Vol. 3. Detroit: Macmillan Reference USA, 2005. 1218-1222. Gale Virtual Reference Library. Web. 29 Dec. 2014. http://go.galegroup.com/ps/retrieve.do?sgHitCountType=None&sort=RELEVANCE&inPS=true&prodId=GVRL&userGroupName=itsbtrial&tabID=T003&searchId=R3&resultListType=RESULT‗LIST&contentSegment=&searchType=BasicSearchForm¤tPosition=9&contentSet=GALE%7CCX3434900431&&docId=GALE|CX3434900431&docType=GALE