Error exponents in hypothesis testing

In statistical hypothesis testing, the error exponent of a hypothesis testing procedure is the rate at which the probabilities of Type I and Type II decay exponentially with the size of the sample used in the test. For example, if the probability of error P e r r o r {\displaystyle P_{\mathrm {error} }} of a test decays as e − n β {\displaystyle e^{-n\beta }} , where n {\displaystyle n} is the sample size, the error exponent is β {\displaystyle \beta } .

Source: Wikipedia — Error exponents in hypothesis testing (CC BY-SA 4.0)

Error exponents in hypothesis testing

In statistical hypothesis testing, the error exponent of a hypothesis testing procedure is the rate at which the probabilities of Type I and Type II decay exponentially with the size of the sample used in the test. For example, if the probability of error P e r r o r {\displaystyle P_{\mathrm {error} }} of a test decays as e − n β {\displaystyle e^{-n\beta }} , where n {\displaystyle n} is the sample size, the error exponent is β {\displaystyle \beta } .

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Source: Wikipedia "Error exponents in hypothesis testing" · CC BY-SA 4.0

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