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In science and statistics, validity is the extent to which a concept, conclusion or measurement is well-founded and corresponds accurately to the real world. The word "valid" is derived from the Latin validus, meaning strong. The validity of a measurement tool (for example, a test in education) is considered to be the degree to which the tool measures what it claims to measure. In psychometrics, validity has a particular application known as test validity: "the degree to which evidence and theory support the interpretations of test scores" ("as entailed by proposed uses of tests"). In the area of scientific research design and experimentation, validity refers to whether a study is able to scientifically answer the questions it is intended to answer. In clinical fields, the assessment of validity of a diagnosis and various diagnostic tests are extremely important. As diagnosis augments treatments, medications, and the patient's life, it is extremely important to know that when running diagnostic tests that clinicians are truly testing what they intend to test. It is generally accepted that the concept of scientific validity addresses the nature of reality and as such is an epistemological and philosophical issue as well as a question of measurement. The use of the term in logic is narrower, relating to the truth of inferences made from premises. Validity is important because it can help determine what types of tests to use, and help to make sure researchers are using methods that are not only ethical, and cost-effective, but also a method that truly measures the idea or construct in question. Source: http://en.wikipedia.org/wiki/Validity_(statistics)
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