Examples of using Type i error in English and their translations into Greek
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Colloquial
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Medicine
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Financial
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Computer
A Type I error occurs when we believe a falsehood("believing a lie").[7]
When comparing two means, concluding the means were different when in reality they were not different would be a Type I error; concluding the means were not different when in reality they were different would be a Type II error. .
A type I error may be likened to a so-called false positive(a result that indicates that a given condition is present when it actually is not present).
A type I error may be compared with a so-called false positive(a result that indicates that a given condition is present when it actually is not present)
Reject Type I error(False Positive)
The terms"type I error" and"type II error" are often used interchangeably with the general notion of false positives
The terms"type I error" and"type II error" are often used interchangeably with the general notion of false positives
Per-family error rate(PFER): the expected number of Type I errors, PFE= E(V).
Avoiding the type I errors(or false negatives)
Two types of error are distinguished: type I error and type II error. .
Assessed by sequential testing strategy designed to control the overall type I error in the trial.
The alpha level is a significance level related to the probability of having a type I error(rejecting a true hypothesis).
The type I error rate or significance level is the probability of rejecting the null hypothesis given that it is true.
GSA-SNP2 provides a greatly improved type I error control by using the SNP-count adjusted gene scores,
The type I error rate or significance level is the probability of rejecting the null hypothesis given that it is true.[5][6]
A Type I error would falsely indicate that treatment A is more effective than the placebo,
i.e., that, the Type I error rate, must be kept at
They're Type I errors.
Type I errors are philosophically a focus of skepticism
Examples of type I errors include a test that shows a patient to have a disease when in fact the patient does not have the disease,