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# Determining Type I error or a Type II error

Suppose we have the following. For each, identify whether it is a Type I error or a Type II error:

1. An individual is told she has cancer but she really doesn't.
2. A person guilty of committing a crime is found innocent in a court of law.
3. An individual is told he doesn't have AIDS, when he really does.
4. A hypothesis test proves one product sells better than another when it really doesn't.
5. A person is found guilty of committing a crime in a court of law when he really didn't commit the crime.
6. A customer satisfaction survey shows that customers are satisfied when they really aren't.
7. A customer satisfaction survey shows that customers are not satisfied when they really are.

Which is worse, a Type I error or a Type II error?

#### Solution Preview

Type I error happens if we reject null hypothesis but it is in fact true. Type II error happens if we fail to reject to null hypothesis but it is in fact wrong.

1. An individual is told she has cancer but she really doesn't.
Type II ...

#### Solution Summary

The solution gives detailed steps on determining if each given statement is justified as a Type I error or a Type II error.

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