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Falling to reject (accepting) a false null hypothesis.

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10y ago

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Related Questions

What happens to the confidence interval if you increase the margin of error?

It depends on whether it is the Type I Error or the Type II Error that is increased.


What is the difference between a Type I error and a Type II error in hypothesis testing?

In hypothesis testing, a Type I error occurs when a true null hypothesis is incorrectly rejected, while a Type II error occurs when a false null hypothesis is not rejected.


Does increasing the margin of error decrease the length of the confidence interval?

It depends on whether it is the Type I Error or the Type II Error that is increased.


When a researcher fails to reject Null Hypothesis when Null Hypothesis is false he has?

made a Type II error.made a Type II error.made a Type II error.made a Type II error.


Is there a direct relationship between the power of a test and the probability of a Type II error?

The power of a test is 1 minus the probability of a Type II error.


If given a sample size reducing the probability of a Type I error will increase the probablility of a Type II error?

Yes.


What is a beta error?

A beta error is another term for a type II error, an instance of accepting the null hypothesis when the null hypothesis is false.


How can the probability of a Type 1 error be reducued?

In some cases a choice of tests may be available; some tests are more powerful than others.Use a larger sample.There is a trade-off between Type I and Type II errors so you can always reduce the Type I error by allowing the Type II error to increase.


If the probability of type 1 error is reduced the probability of type 2 error is also reduced?

No....the two are mirror images of each other. Reducing type I would increase type II


Type 1 error and type 2 error?

In statistics: type 1 error is when you reject the null hypothesis but it is actually true. Type 2 is when you fail to reject the null hypothesis but it is actually false. Statistical DecisionTrue State of the Null HypothesisH0 TrueH0 FalseReject H0Type I errorCorrectDo not Reject H0CorrectType II error


Reduce type 1 error?

Accept lower p-values (meaning lower in magnitude; values tending toward zero).--And don't forget that by reducing the probability of getting a type I error, you increase the probability of getting a type II error (inverse relationship).


What is Hypothesis Testing of Type II Error?

Failing to reject a false null hypothesis.