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Validity is the main extent to which a concept, conclusion, or measurement is well-founded and likely corresponds accurately to the real world. [1] [2] The word "valid" is derived from the Latin validus, meaning strong.
Test validity is the extent to which a test (such as a chemical, physical, or scholastic test) accurately measures what it is supposed to measure.In the fields of psychological testing and educational testing, "validity refers to the degree to which evidence and theory support the interpretations of test scores entailed by proposed uses of tests". [1]
The validity of an argument can be tested, proved or disproved, and depends on its logical form. [3] Arguments. Argument terminology used in logic.
Test validity, validity in educational and psychological testing; Face validity, the property of a test intended to measure something; Construct validity, refers to whether a scale measures or correlates with the theorized psychological construct it measures; Content validity, the extent to which a measure represents all facets of a given construct
Construct validity concerns how well a set of indicators represent or reflect a concept that is not directly measurable. [1] [2] [3] Construct validation is the accumulation of evidence to support the interpretation of what a measure reflects.
Satisfiability and validity are defined for a single formula, but can be generalized to an arbitrary theory or set of formulas: a theory is satisfiable if at least one interpretation makes every formula in the theory true, and valid if every formula is true in every interpretation.
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
Internal validity, therefore, is more a matter of degree than of either-or, and that is exactly why research designs other than true experiments may also yield results with a high degree of internal validity. In order to allow for inferences with a high degree of internal validity, precautions may be taken during the design of the study.