2. Type I and Type ll Errors: A Digression Type I error: the error of rejecting a hypothesis when it is true Type II error: the error of accepting a false hypothesis Type I error= a=prob (rejecting Ho I Ho is true) Type II error=B=prob(accepting Ho Ho is false) The classical approach to deal with type I, type lI problems -To assume a type I error is more serious than a type ll error, try to keep the prob. of committing a type I error at a fairly low level, and then minimize a type Il error as much as possible. That is, simply specifies the value of a without worrying too much about B The decision to accept or reject a null hypothesis depends critically on both the d f. and the probability of committing a type I error A% confidence coefficient/a 5% level of significance/a 95%level or degree of confidence: we are prepared to accept at the most a 5 percent probability of committing a type I error2. Type I and Type II Errors: A Digression Type I error: the error of rejecting a hypothesiswhen it is true. Type II error: the error of accepting a false hypothesis. Type I error=α=prob.(rejectingH0 |H0 is true) Type II error=β=prob.(acceptingH0 |H0 is false) The classical approach to deal with type I, type II problems: ——To assume a type I error is more serious than a type II error, try to keep the prob. of committing a type I error at a fairly low level, and then minimize a type II error as much as possible. That is, simply specifies the value ofαwithout worrying too much aboutβ. The decision to accept or reject a null hypothesis depends critically on both the d.f. and the probability of committing a type I error. A 95% confidence coefficient/a 5% level of significance/a 95% level or degree of confidence: we are prepared to accept at the most a 5 percent probability of committing a type I error