Explanations and Measurement

An explanation is a structured set of precise, often symbolic statements generally constructed in order to explain a given set of facts, the reasons for those facts, and the consequences of those facts as related to other things, events, or concepts. In science, an explanation is used to test hypotheses, support predictions, or simply to explain the scientific methods or results. This explanation can also explain the existing rules or principles in regards to some physical objects, phenomena, or even laws. The explanation is then made precise in order to be tested against observations, theories, or contrary evidence.

Measurement – Research Methods Knowledge Base

There are two basic types of explanation: deductive-nomological explanation and inductive-deductive explanation. A deductive explanation involves the classifications, structure, and/or explanation of concepts. For example, if we study the chemical properties of orange juice, we would first have to construct a list of the properties that the orange juice has, a list of the properties it can possess when combined with other properties, an explanation of how these properties can be subsumed by the properties of the juice itself, and a further explanation that these properties are necessary for the Juice to possess. Once we have constructed the list of the necessary and sufficient properties, we can use deductive arguments to infer the rest.

An inductive explanation is quite the opposite. In an inductive explanation, there is no need to construct or justify any sets of ideas, concepts, or premises in order to explain phenomena. Scientific explanations, on the other hand, require strong logical and predictive claims. In order for a scientific explanation to be accepted by the scientific community, it must make sense, be consistent, provide testable predictions, be reasonable from a scientific standpoint (e.g., it should not produce inconsistent results), it should be able to accommodate possible conflicting interpretations, it should be plausible given known facts about the phenomena under study, it should be testable, and it should have a wider appeal than its competitor explanations. If all of these criteria are met, then the rival explanation will more than likely have to drop out of the picture.

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