Passive observational studies that are conducted on diverse groups of people in real-world situations tend to be very high in external validity.
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By contrast, however, the very strategies employed to control these factors may also limit the generalizability or External Validity of the findings.
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If the experimental environment is too artificial it can damage external validity in an ideal observer experiment that makes use of natural scene statistics.
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Findings from behavioral game theory will tend to have higher external validity and can be better applied to real world decision-making behavior.
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External Validity refers to the extent to which a set of research findings provides an accurate description of what typically happens in the real world.
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This form of external validity has to do with the degree to which a set of research findings applies to real world settings or contexts.
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The second is experimental validity ( or External validity ), the degree to which a study supports the intended conclusion drawn from the results.
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There is usually a trade-off between experimental control ( internal validity ) and being able to generalize to the population ( external validity ).
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While gaining internal validity ( excluding interfering variables by keeping them constant ) you lose ecological or external validity because you establish an artificial laboratory setting.
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External Validity is very important when it comes to statistical research because you want to make sure that you have a correct depiction of the population.
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