Concept of scientific method and scientific inquiry model.

Scientific method

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Scientific method refers to the process of research, learning and correcting or integrating past knowledge. In order to be "scientific", an investigative process must be carefully, observable, and determining the basis of which the argument can be applied. A scientific Data collection and project (hypothe ses) include formulation-testing.

Although there may be differences in the characteristics of the scientific method due to the diversity of search, some special features distinguish the scientific method from other theoretical processes. Scientists formulate a project to explain any illumination and through research, these projects are tested. The repetition of the research steps is necessary, otherwise the results of the test and the decision will be questioned. If necessary, any theory can build multiple projects in the same thread. This can result in newer projects being implemented and various teams of the project can be relevant. One of the key features of the scientific method is to be neutral and impersonal, and the research process should be kept open so that any specialist in any part of the world can evaluate the research. By doing so, other scientists can verify the same project repeatedly by getting the same result.

Scientific inquiry model

Classroom model

Aristotle first helped to create a classical model. He first distinguished between approximate and exact argument, explaining abductive reasoning, ascending argument and introductory reasoning, and thinking about the reasoning with the analogy.

Technical model

In 1877, Charles Sanders characterized Pars Search as the fact that it is not really seeking the truth, but having an uncertain belief from a sudden event or controversy arising from an uncertain belief, a belief based on which a decision can be made. This is a broad form. He outlines the four methods of reconciliation, which is more effective than less effective: -

• To stand firm in your own opinion, like obstinacy, to ignore the opposite, the truth is that it is a personal matter of nature.
• Discuss the differences by force
• Restricted thinking within the existing scientific paradigm.
• The scientific method - which seems to be delusional, verifies itself and correctes itself by correcting it and trying its best.

Perce believed that the process of judicial process in real-field is inferior to intuition, custom and emotionalism, scientific method is applicable only for theoretical research. In fact, theoretical research should not be used to draw practical matters. The success of scientific method is that it helps to arrive at some definite beliefs based on which the most effective decisions can be made. Pursuing this concept by noting that self-realization of man, rather than finding uncertainty, Pars has shown that these uncertainties lead man to the path of truth, people then see the truth as an opinion whose application will guide them to the goal of the opinion, they will not miss them.

Parse believes that the rational inquiry is not only based on the fact that the reality and the realities are not, it also shapes them. Using logic means assuming that the truth is invisible and independent of our diverse opinion. He defined the truth as unity between proposals and suggestions. In his view, the truth is not the consensus of a particular society, so that the research experts are transformed into the opinion polls, the truth is something that can be discovered by science judges. Someone may discover it before and someone may discover later, everyone may start searching from different angles, but everyone will get the same conclusions.

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Functional logic and various subsections of computer science, such as artificial intelligence, machine learning, machine learning theory, inferential statistics, and knowledge representation, calculation based on assumptions related to scientific research, Works on formulating logical and statistical structures. They specially contribute to project preparation, logical downward and technical testing. Some of these uses constitute the ability to predict the distribution of experience by distributing complexity measurements used in algorithmic information.

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