type II error


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type II error

n. Statistics
The error of failing to reject a null hypothesis that is false. Also called beta error.

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
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Type I error is more costly for banks than the type II error because it will cause non-performing loans, consequently lost profits, higher provisions, and higher credit costs.
The width of control limits is determined by considering the tradeoff between the required type I error rate and expected type II error rate.
To avoid a Type II error, he immediately went to the Old Faithful factory, shut it down, and impounded all the beans in the warehouse.
1) in the degree of correlation of the covariance matrices of the two groups of variables, which decreases the probability of making a type II error.
The type II error or false negative beta ([beta]) is the error in freeing the guilty or failing to conclude the treatments differ, when, in fact, they are different.
there is a price impact), we will make a Type II error anytime the return from the price-impact distribution is to the right of the lower critical value return but to the left of the upper critical value return.
The computed type I and type II error are the expected or the theoretical percentage error of prediction tor the population.
When we implement the overall system innovation model testing, to ensure the probability of success in bias detection, we should control the probabilities of committing both type I error [alpha] and type II error [beta] which correspond to the probabilities of making wrong decisions during test [16, 17].
The former, ignoring the presence of the predator when it really was there, constitutes a Type II error, or a false negative.
Consequently, it would have to make either Decision 3 or Decision 4, which corresponds to Type I error or Type II error, respectively.