| type II error |
The researcher's data-based decision that the null hypothesis is true when it is really false. While this incorrect conclusion could be the result of bad luck as in the case of a Type I Error, a more worrisome possibility is that the experiment had low power.
출처: instructional1.calstatela.edu/dweiss/Psy302/Glossa...
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| type I error |
Also known as "false positive" or "alpha error." An incorrect judgment or conclusion that occurs when an association is found between variables where, in fact, no association exists. In an experiment, for example, if the experimental procedure does not really have any effect, chance or random error may cause the researcher to conclude that the experimental procedure did have an effect.
출처: www.utmem.edu/CENTER/cgi/htmlos.cgi/004579.71.1265...
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| type II error |
Also known as "false negative" or "beta error." An incorrect judgement or conclusion that occurs when no association is found between variables where in fact, an association does exist. In a medical screening, for example, a negative test result may occur by chance in a subject who possesses the attribute for which the test is conducted.
출처: www.utmem.edu/CENTER/cgi/htmlos.cgi/004579.71.1265...
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| type II error |
accepting the null hypothesis when it is false.
출처: www.socialresearchmethods.net/tutorial/Colosi/lcol...
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| type II error |
acceptance of the null hypothesis when it should be rejected.
출처: hudsonmediaresearch.com/glossary_of_research_terms...
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