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# How is type 1 error more dangerous then type 2 error in statistics?

Statistics for science.

### 3 Answers

- statmanLv 61 decade agoFavorite Answer
A type 1 error is seeing a difference when there really isn't one.

A type 2 error is not seeing a difference when there is one.

As an example, suppose our hypothesis is "This individual does not have cancer." A type 1 error would be to conclude that the individual has cancer, when they really don't. A type 2 error would be to conclude that the individual doesn't have cancer, when they really do.

To me, both of these situations are dangerous. In one case the patient receives unnecessary treatment. In the other, the patient doesn't receive needed treatment.

Here's another example. Suppose our hypothesis is "This material is not radioactive." A type 1 error would be to conclude that the material is radioactive, when it really isn't. A type 2 error would be to conclude that the material is not radioactive, when it really is.

In this case, the type 2 error is more dangerous.

Finally, here is a really vivid example. Suppose our hypothesis is "This gun isn't loaded." A type 1 error would be to conclude that is loaded, when it really isn't. A type 2 error would be to conclude it isn't loaded, when it really is. The type 2 error is clearly more dangerous!

In general, a type 1 error is not more dangerous than a type 2 error. It depends on the nature of your hypothesis.

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- crichlowLv 44 years ago
b form I is once you're making a "pretend sensible." rejecting the null at the same time as that's authentic. form II is once you're making a "pretend detrimental." once you do not reject the null and the alternative is authentic or accepting the null at the same time as that's pretend.

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