Type I and Type II errors, when you are testing a hypothesis, there is the possi

Question

Type I and Type II errors, when you are testing a hypothesis, there is the possibility your conclusion is incorrect. You could reject your null hypothesis when it's actually true (Type I error), or you could not reject the null hypothesis when the alternative is true (Type II error). You can think of this in terms of a trial. If the jury puts an innocent man in jail, this is a Type I error. If the jury lets a guilty person go free, this is a Type II error.

Someone tells you something and you need to decide if you should believe him or her. Are you more likely to be worried about committing a Type I error or a Type II error?

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Explanation / Answer

In this situation, Type I error is when we do not believe the other person, but he or she is telling the truth and Type II error is when we believe him, but he or she is not telling the truth.

In case of Type I error, when we do not believe the other person, we will try to find the truth by ourselves and chances are that with some effort, we will find out the truth. So Type I error results in some additional effort, but it does not pose a serious risk of relying on false information. Therefore, we would not be worried about committing a Type I error.

However, in case of Type II error, when we believed the other person, there can be serious consequences of relying on false information provided by the other person. Hence we would be worried about committing a Type II error.

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