Question

Give an example of a situation in which you believe a Type 1 Error is more serious than a Type II Error. Give an example of situation in which you believe a Type II Error is more serious than a Type 1 Error. In each case, why do you think so?

Answer 1

Type I errors in statistics occur when statisticians incorrectly reject the null hypothesis, or statement of no effect, when the null hypothesis is true while Type II errors occur when statisticians fail to reject the null hypothesis and the alternative hypothesis, or the statement for which the test is being conducted to provide evidence in support of, is true.

In other words ,simply we can say that. Type one error is rejection of right thing .and type two error is accepting. Wrong thing .

Suppose you are designing a medical screening for a disease. A false positive of a Type I error may give a patient some anxiety, but this will lead to other testing procedures which will ultimately reveal the initial test was incorrect. In contrast, a false negative from a Type II error would give a patient the incorrect assurance that he or she does not have a disease when he or she in fact does. As a result of this incorrect information, the disease would not be treated. If doctors could choose between these two options, a false positive is more desirable than a false negative.

Now suppose that someone had been put on trial for murder. The null hypothesis here is that the person is not guilty. A Type I error would occur if the person were found guilty of a murder that he or she did not commit, which would be a very serious outcome for the defendant. On the other hand, a Type II error would occur if the jury finds the person not guilty even though he or she committed the murder, which is a great outcome for the defendant but not for society as a whole

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