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Internal and external validity

Last updated on Wednesday, April 24, 2024.

 

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Internal validity refers to the extent to which a study's design and methods accurately answer the research question being investigated, without the influence of other factors. External validity, on the other hand, refers to the generalizability of the study's findings to other populations, settings, or conditions beyond the specific parameters of the research.

Understanding Internal and External Validity in Research

Internal Validity

Internal validity refers to the extent to which a study is conducted in such a way that it establishes a trustworthy cause-and-effect relationship between the variables being studied. In the realm of computer science and artificial intelligence, internal validity is crucial for ensuring that experimental findings are valid and reliable.

External Validity

External validity pertains to the generalizability of the findings of a study to other populations, settings, and conditions. It is essential to consider external validity when conducting research in computer science and artificial intelligence to ensure that the results can be applied beyond the specific context of the study.

Internal and external validity are intertwined concepts that are fundamental to the scientific process. While internal validity ensures that the study's design and methodology support the conclusions drawn, external validity enables researchers to apply those conclusions to broader contexts and real-world scenarios.

 

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