| type II error |
An error of statistical inference when the null hypothesis is retained when it is false. This is an error of "not seeing enough in the data."
출처: psy.st-andrews.ac.uk/resources/glossary.shtml
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|---|---|
| type I error |
(alpha error) A rejection of a hypothesis when it is true. An example of Type 1 Error is finding a substance present when it is not.
출처: www.atlab.com/LIMS/glossaryp-t.html
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| type II error |
(beta error) An acceptance of a hypothesis when it is false. An example of Type II Error is not finding a substance present when it is present.
출처: www.atlab.com/LIMS/glossaryp-t.html
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| type I error |
The null hypothesis is rejected even though it is true.
출처: srmwww.gov.bc.ca/wildlife/wsi/glossary.html
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| type I error |
Mistakenly rejecting the null hypothesis when it is actually true. The maximum probability of making a Type I error that the researcher is willing to accept is call alpha (a). Alpha is determined before the study begins. False positive conclusion. Studies commonly set alpha to 1 in 20 (=0.05).
출처: www.musc.edu/dc/icrebm/statisticalsignificance.htm...
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