<P> In statistical hypothesis testing , a type I error is the rejection of a true null hypothesis ( also known as a `` false positive '' finding ) , while a type II error is failing to reject a false null hypothesis ( also known as a `` false negative '' finding ) . More simply stated , a type I error is to falsely infer the existence of something that is not there , while a type II error is to falsely infer the absence of something that is . </P>
<P> In statistical hypothesis testing , a type I error is the rejection of a true null hypothesis ( also known as a `` false positive '' finding ) , while a type II error is failing to reject a false null hypothesis ( also known as a `` false negative '' finding ) . More simply stated , a type I error is to falsely infer the existence of something that is not there , while a type II error is to falsely infer the absence of something that is . </P>
when does a type 1 error occur in statistics
when does a type 1 error occur in statistics
the rejection of a true null hypothesis
the rejection of a true null hypothesis