![]() When observed effects are under the influence of or confounded by extraneous variable, then it would be difficult to draw valid conclusions, about the relationship between variables. It gauges whether the independent variables cause the observed effects on the dependent variables or not. In statistics, internal validity is used to mean the measure of accuracy, which checks the soundness of the experiment, specifically regarding confounding. It checks whether the casual relationship discovered in the experiment can be generalized or not.Ĭan the outcome of the research be applied to the real world?ĭegree to which the conclusion is warranted.ĭegree to which the study is warranted to generalize the result to other context.Īddress or eliminate alternative explanation for the result. It is a measure of accuracy of the experiment. ![]() Internal validity is the extent to which the experiment is free from errors and any difference in measurement is due to independent variable and nothing else.Įxternal validity is the extent to which the research results can be inferred to world at large. ![]() ![]() Content: Internal Validity Vs External Validity To further comprehend the topic, check out this article. ![]() The basic difference between internal and external validity is that the former talks about the relationship between variables whereas the latter is concerned with the universality of the results. ![]()
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