Linear Plexing

We have fixed $\\alpha$ as the maximum acceptable probability of commiting atype $I$ error. But associated with each normalized test of significance is $\\gamma$ , the probability of commiting a type $I$ error.

Notice that as we make $\\gamma$ smaller, the smaller the critical regionbecomes and thus the larger the value of the test statistic must be for thenull hypothesis to be rejected.

Find $p$ , defined as the smallest $\\gamma$ for which we can still reject $H_{0}$ .

Reject $H_{0}$ if $\\alpha<p$ .

单词	LinearPlexing
释义	Linear Plexing We have fixed $\\alpha$ as the maximum acceptable probability of commiting atype $I$ error. But associated with each normalized test of significance is $\\gamma$ , the probability of commiting a type $I$ error. Notice that as we make $\\gamma$ smaller, the smaller the critical regionbecomes and thus the larger the value of the test statistic must be for thenull hypothesis to be rejected. Find $p$ , defined as the smallest $\\gamma$ for which we can still reject $H_{0}$ . Reject $H_{0}$ if $\\alpha<p$ .
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