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The phrase "type I errors" is correct and commonly used in written English.
It is typically used in the context of statistical analysis and hypothesis testing. Example: In this study, we focused on identifying and minimizing type I errors, as they can lead to incorrect conclusions and wasted resources.
Dictionary
type I errors
noun
Plural of type I error
Exact(60)
Science traditionally aims at avoiding type I errors.
With corrections for baseline trend, fewer Type I errors were made.
Simulation studies show that empirical powers and type I errors are close to their nominal levels.
A risk of 5% for type I errors and 20% for type II errors was accepted.
The main idea is to control for the marginal type I errors of response rate and toxicity rate separately.
Without statistical adjustments to correct for baseline trend, Type I errors greatly increased as baseline trend increased.
The merit of the three methods is explored by calculation and comparison of power and of type I errors.
Finally, proteomic analyses are prone to Type I errors.
The Bonferroni's correction (0.05/test numbers) [45] was used to avoid type I errors.
Since this study employs multiple phenotypic scales, the potential exists for type I errors.
Multiple testing involves the risk of committing type I errors [57].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com