A scientific theory is empirical,[citation needed] and is always open to falsification if new evidence is presented. That is, no theory is ever considered strictly certain as science accepts the concept of fallibilism.[citation needed] The philosopher of science Karl Popper
sharply distinguishes truth from certainty. He writes that scientific
knowledge "consists in the search for truth", but it "is not the search
for certainty ... All human knowledge is fallible and therefore
uncertain."
New scientific knowledge rarely results in vast changes in our understanding. According to psychologist Keith Stanovich, it may be the media's overuse of words like "breakthrough" that leads the public to imagine that science is constantly proving everything it thought was true to be false.While there are such famous cases as the theory of relativity that required a complete reconceptualization, these are extreme exceptions. Knowledge in science is gained by a gradual synthesis of information from different experiments, by various researchers, across different branches of science; it is more like a climb than a leap. Theories vary in the extent to which they have been tested and verified, as well as their acceptance in the scientific community.For example, heliocentric theory, the theory of evolution, relativity theory, and germ theory still bear the name "theory" even though, in practice, they are considered factual. Philosopher Barry Stroud adds that, although the best definition for "knowledge" is contested, being skeptical and entertaining the possibility that one is incorrect is compatible with being correct. Ironically then, the scientist adhering to proper scientific approaches will doubt themselves even once they possess the truth. The fallibilist C. S. Peirce argued that inquiry is the struggle to resolve actual doubt and that merely quarrelsome, verbal, or hyperbolic doubt is fruitless—but also that the inquirer should try to attain genuine doubt rather than resting uncritically on common sense He held that the successful sciences trust, not to any single chain of inference (no stronger than its weakest link), but to the cable of multiple and various arguments intimately connected.
Stanovich also asserts that science avoids searching for a "magic bullet"; it avoids the single-cause fallacy. This means a scientist would not ask merely "What is the cause of ...", but rather "What are the most significant causes of ...". This is especially the case in the more macroscopic fields of science (e.g. psychology, cosmology). Of course, research often analyzes few factors at once, but these are always added to the long list of factors that are most important to consider.For example: knowing the details of only a person's genetics, or their history and upbringing, or the current situation may not explain a behaviour, but a deep understanding of all these variables combined can be very predictive.
There also can be an element of political or ideological bias on all sides of scientific debates.[citation needed] Sometimes, research may be characterized as "bad science", research that may be well-intentioned but is actually incorrect, obsolete, incomplete, or over-simplified expositions of scientific ideas. The term "scientific misconduct" refers to situations such as where researchers have intentionally misrepresented their published data or have purposely given credit for a discovery to the wrong person.
Astronomy became much more accurate after Tycho Brahe devised his
scientific instruments for measuring angles between two celestial
bodies, before the invention of the telescope. Brahe's observations were
the basis for Kepler's laws.
John Ziman points out that intersubjective pattern recognition is fundamental to the creation of all scientific knowledge.Ziman shows how scientists can identify patterns to each other across centuries: Needham 1954 (illustration facing page 164) shows how today's trained Western botanist can identify Artemisia alba from images taken from a 16th-century Chinese pharmacopeia, and Ziman refers to this ability as 'perceptual consensibility'. Ziman then makes consensibility, leading to consensus, the touchstone of reliable knowledge.
When a hypothesis proves unsatisfactory, it is either modified or discarded. If the hypothesis survived testing, it may become adopted into the framework of a scientific theory. This is a logically reasoned, self-consistent model or framework for describing the behavior of certain natural phenomena. A theory typically describes the behavior of much broader sets of phenomena than a hypothesis; commonly, a large number of hypotheses can be logically bound together by a single theory. Thus a theory is a hypothesis explaining various other hypotheses. In that vein, theories are formulated according to most of the same scientific principles as hypotheses. In addition to testing hypotheses, scientists may also generate a model based on observed phenomena. This is an attempt to describe or depict the phenomenon in terms of a logical, physical or mathematical representation and to generate new hypotheses that can be tested.
While performing experiments to test hypotheses, scientists may have a preference for one outcome over another, and so it is important to ensure that science as a whole can eliminate this bias. This can be achieved by careful experimental design, transparency, and a thorough peer review process of the experimental results as well as any conclusions. After the results of an experiment are announced or published, it is normal practice for independent researchers to double-check how the research was performed, and to follow up by performing similar experiments to determine how dependable the results might be. Taken in its entirety, the scientific method allows for highly creative problem solving while minimizing any effects of subjective bias on the part of its users (namely the confirmation bias)
Statistical methods, which are mathematical techniques for summarizing and analyzing data, allow scientists to assess the level of reliability and the range of variation in experimental results. Statistical analysis plays a fundamental role in many areas of both the natural sciences and social sciences.
Computational science applies computing power to simulate real-world situations, enabling a better understanding of scientific problems than formal mathematics alone can achieve. According to the Society for Industrial and Applied Mathematics, computation is now as important as theory and experiment in advancing scientific knowledge.
Whether mathematics itself is properly classified as science has been a matter of some debate. Some thinkers see mathematicians as scientists, regarding physical experiments as inessential or mathematical proofs as equivalent to experiments. Others do not see mathematics as a science, since it does not require an experimental test of its theories and hypotheses. Mathematical theorems and formulas are obtained by logical derivations which presume axiomatic systems, rather than the combination of empirical observation and logical reasoning that has come to be known as the scientific method. In general, mathematics is classified as formal science, while natural and social sciences are classified as empirical sciences.
New scientific knowledge rarely results in vast changes in our understanding. According to psychologist Keith Stanovich, it may be the media's overuse of words like "breakthrough" that leads the public to imagine that science is constantly proving everything it thought was true to be false.While there are such famous cases as the theory of relativity that required a complete reconceptualization, these are extreme exceptions. Knowledge in science is gained by a gradual synthesis of information from different experiments, by various researchers, across different branches of science; it is more like a climb than a leap. Theories vary in the extent to which they have been tested and verified, as well as their acceptance in the scientific community.For example, heliocentric theory, the theory of evolution, relativity theory, and germ theory still bear the name "theory" even though, in practice, they are considered factual. Philosopher Barry Stroud adds that, although the best definition for "knowledge" is contested, being skeptical and entertaining the possibility that one is incorrect is compatible with being correct. Ironically then, the scientist adhering to proper scientific approaches will doubt themselves even once they possess the truth. The fallibilist C. S. Peirce argued that inquiry is the struggle to resolve actual doubt and that merely quarrelsome, verbal, or hyperbolic doubt is fruitless—but also that the inquirer should try to attain genuine doubt rather than resting uncritically on common sense He held that the successful sciences trust, not to any single chain of inference (no stronger than its weakest link), but to the cable of multiple and various arguments intimately connected.
Stanovich also asserts that science avoids searching for a "magic bullet"; it avoids the single-cause fallacy. This means a scientist would not ask merely "What is the cause of ...", but rather "What are the most significant causes of ...". This is especially the case in the more macroscopic fields of science (e.g. psychology, cosmology). Of course, research often analyzes few factors at once, but these are always added to the long list of factors that are most important to consider.For example: knowing the details of only a person's genetics, or their history and upbringing, or the current situation may not explain a behaviour, but a deep understanding of all these variables combined can be very predictive.
Pseudoscience, fringe science, and junk science
An area of study or speculation that masquerades as science in an attempt to claim a legitimacy that it would not otherwise be able to achieve is sometimes referred to as pseudoscience, fringe science, or junk science Physicist Richard Feynman coined the term "cargo cult science" for cases in which researchers believe they are doing science because their activities have the outward appearance of science but actually lack the "kind of utter honesty" that allows their results to be rigorously evaluated. Various types of commercial advertising, ranging from hype to fraud, may fall into these categories.There also can be an element of political or ideological bias on all sides of scientific debates.[citation needed] Sometimes, research may be characterized as "bad science", research that may be well-intentioned but is actually incorrect, obsolete, incomplete, or over-simplified expositions of scientific ideas. The term "scientific misconduct" refers to situations such as where researchers have intentionally misrepresented their published data or have purposely given credit for a discovery to the wrong person.
Scientific practice
"If a man will begin with certainties, he shall end in doubts; but if he will be content to begin with doubts, he shall end in certainties." —Francis Bacon (1605) The Advancement of Learning, Book 1, v, 8A skeptical point of view, demanding a method of proof, was the practical position taken as early as 1000 years ago, with Alhazen, Doubts Concerning Ptolemy, through Bacon (1605), and C. S. Peirce (1839–1914), who note that a community will then spring up to address these points of uncertainty. The methods of inquiry into a problem have been known for thousands of years, and extend beyond theory to practice. The use of measurements, for example, is a practical approach to settle disputes in the community.
John Ziman points out that intersubjective pattern recognition is fundamental to the creation of all scientific knowledge.Ziman shows how scientists can identify patterns to each other across centuries: Needham 1954 (illustration facing page 164) shows how today's trained Western botanist can identify Artemisia alba from images taken from a 16th-century Chinese pharmacopeia, and Ziman refers to this ability as 'perceptual consensibility'. Ziman then makes consensibility, leading to consensus, the touchstone of reliable knowledge.
The scientific method
Main article: Scientific method
The scientific method seeks to explain the events of nature in a reproducible way.An
explanatory thought experiment or hypothesis is put forward, as
explanation, using principles such as parsimony (also known as "Occam's
Razor") and are generally expected to seek consilience—fitting well with
other accepted facts related to the phenomena. This new explanation is used to make falsifiable
predictions that are testable by experiment or observation. The
predictions are to be posted before a confirming experiment or
observation is sought, as proof that no tampering has occurred. Disproof
of a prediction is evidence of progress.This is done partly through observation of natural phenomena, but also
through experimentation, that tries to simulate natural events under
controlled conditions, as appropriate to the discipline (in the
observational sciences, such as astronomy or geology, a predicted
observation might take the place of a controlled experiment).
Experimentation is especially important in science to help establish causal relationships (to avoid the correlation fallacy).When a hypothesis proves unsatisfactory, it is either modified or discarded. If the hypothesis survived testing, it may become adopted into the framework of a scientific theory. This is a logically reasoned, self-consistent model or framework for describing the behavior of certain natural phenomena. A theory typically describes the behavior of much broader sets of phenomena than a hypothesis; commonly, a large number of hypotheses can be logically bound together by a single theory. Thus a theory is a hypothesis explaining various other hypotheses. In that vein, theories are formulated according to most of the same scientific principles as hypotheses. In addition to testing hypotheses, scientists may also generate a model based on observed phenomena. This is an attempt to describe or depict the phenomenon in terms of a logical, physical or mathematical representation and to generate new hypotheses that can be tested.
While performing experiments to test hypotheses, scientists may have a preference for one outcome over another, and so it is important to ensure that science as a whole can eliminate this bias. This can be achieved by careful experimental design, transparency, and a thorough peer review process of the experimental results as well as any conclusions. After the results of an experiment are announced or published, it is normal practice for independent researchers to double-check how the research was performed, and to follow up by performing similar experiments to determine how dependable the results might be. Taken in its entirety, the scientific method allows for highly creative problem solving while minimizing any effects of subjective bias on the part of its users (namely the confirmation bias)
Mathematics and formal sciences
Main article: Mathematics
Mathematics
is essential to the sciences. One important function of mathematics in
science is the role it plays in the expression of scientific models.
Observing and collecting measurements, as well as hypothesizing and
predicting, often require extensive use of mathematics. Arithmetic,
algebra, geometry, trigonometry and calculus, for example, are all
essential to physics. Virtually every branch of mathematics has
applications in science, including "pure" areas such as number theory
and topology.Statistical methods, which are mathematical techniques for summarizing and analyzing data, allow scientists to assess the level of reliability and the range of variation in experimental results. Statistical analysis plays a fundamental role in many areas of both the natural sciences and social sciences.
Computational science applies computing power to simulate real-world situations, enabling a better understanding of scientific problems than formal mathematics alone can achieve. According to the Society for Industrial and Applied Mathematics, computation is now as important as theory and experiment in advancing scientific knowledge.
Whether mathematics itself is properly classified as science has been a matter of some debate. Some thinkers see mathematicians as scientists, regarding physical experiments as inessential or mathematical proofs as equivalent to experiments. Others do not see mathematics as a science, since it does not require an experimental test of its theories and hypotheses. Mathematical theorems and formulas are obtained by logical derivations which presume axiomatic systems, rather than the combination of empirical observation and logical reasoning that has come to be known as the scientific method. In general, mathematics is classified as formal science, while natural and social sciences are classified as empirical sciences.
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