Type I error


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Type I error

A Type I error is a false positive in a test outcome where something is falsely inferred to exist. This usually means incorrectly rejecting the null hypothesis (H0), which is the testing statement that whatever is being studied has no statistically significant effect on the problem.

An example would be a drug trial that incorrectly concludes the prescribed medication cured the patient’s ailment, when in fact the disease symptoms were missed in subsequent exams or some other treatment cured the patient.



Source : DeepAI.org



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