type II error


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type II error

[‚tīp ′tü ‚er·ər]
(statistics)
One of two types of error in testing hypotheses: incorrectly accepting the hypothesis tested when an alternate hypothesis is true. Also known as error of the second kind.
References in periodicals archive ?
The type I error occurs when the control chart shows a point falling beyond the control limits or points forming non-random patterns, when no assignable cause of variation is present; the type II error occurs when the control chart fails to detect an out-of-control process.
However, strong sensitivity to Type II errors increases the likelihood of Type I errors, which in this case would be the turning away (whether temporarily or permanently) of benign travelers at a cost to both those travelers and the United States.
b] is critical value corresponding to Type II error rate, d is effect size or the minimal detectable difference, and s is the standard deviation for the primary outcome.
The type I error from the contingency table was therefore, 11/25 or 44 per cent and the type II error was 12/25 or 48 per cent.
It has a strong relation with the alternative hypothesis and size of type II error [beta] the probability of accepting null hypothesis when [H.
The problem is that assessing the difference between a Type I and a Type II error is highly problematic--especially in the split-second timing that often determined the difference between life and death in our ancestral environments--so the default position is to assume that all patterns are real; that is, assume that all rustles in the grass are dangerous predators and not the wind.
If we go forward to the first quarter of 2011, the type I error is estimated to be 93 percent, while the type II error is estimated to be 17 percent.
They found no link between religious coping and the use of psychostimulants but warned that their analysis on psychostimulants may have been prone to type II error and should be interpreted with caution.
The chance of a Type II error can be directly reduced by increasing the sample size.
As shown in Table 2, while standard errors varied by just 16% across the models, a Type II error was an artifact of the wide variation in regression coefficients (63% difference) between the weighted and unweighted models.