type II error

Also found in: Medical, Legal, Financial, Encyclopedia, Wikipedia.

type II error

n. Statistics
The error of failing to reject a null hypothesis that is false. Also called beta error.
American Heritage® Dictionary of the English Language, Fifth Edition. Copyright © 2016 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. All rights reserved.

type II error

n
(Statistics) statistics the error of not rejecting the null hypothesis when it is false. The probability of avoiding such an error is the power of the test and is a function of the alternative hypothesis
Collins English Dictionary – Complete and Unabridged, 12th Edition 2014 © HarperCollins Publishers 1991, 1994, 1998, 2000, 2003, 2006, 2007, 2009, 2011, 2014
Mentioned in
References in periodicals archive
In sum, the ecological approach fails due to a Type II error (accepting the null hypothesis when it is false), which means believing that the available data for decisionmaking are too uncertain from a Knightian perspective to commit substantial resources or commit to irrevocable courses of action in seeking to mitigate climate change.
Low statistical power contributes to an increased likelihood of making a Type II error (Onwuegbuzie, 2004), thereby causing important findings to be either misreported or not even published.
Incorrectly rejecting the null hypothesis is called Type I error and incorrectly accepting the null hypothesis is called Type II error. For every statistical test, the probability of type I error is called [alpha] and the probability of type II error is called [beta] as it is shown in table 1.
Power of the study (1-[beta]) ([beta] is type II error) (Usually 1-[beta] is fixed at > 80%)
Type I and Type II error concerns in fMRI research: re-balancing the scale.
In the first place, even if any single Type I error is always more costly than a single Type II error, what matters is the total social cost of all errors, not the cost of any individual error or the relative costs of any two.
A Type II error takes place when the regression coefficient for level or slope change has a p value > .05 in data series with intervention effect.
Failing to reject [H.sub.o], under the constraints of committing a Type I or Type II error, is a better decision than simply accepting it, even though the two choices appear to give a similar conclusion.
Type I and Type II errors. The proportion of cases in which visual analysts detect a nonexistent effect (i.e., commit a Type I error) or miss an existing effect (i.e., a Type II error) can be used as an indicator of their performance.
It is apparent that the misclassification costs associated with Type I error (a customer with good credit is misclassified as a customer with bad credit) and Type II error (a customer with bad credit is misclassified as a customer with good credit) are significantly different.
Copyright © 2003-2025 Farlex, Inc Disclaimer
All content on this website, including dictionary, thesaurus, literature, geography, and other reference data is for informational purposes only. This information should not be considered complete, up to date, and is not intended to be used in place of a visit, consultation, or advice of a legal, medical, or any other professional.