![]() ![]() Suppose the null hypothesis, H 0, is: Frank’s rock climbing equipment is safe. Increasing the sample size can increase the Power of the Test. Ideally, we want a high power that is as close to one as possible. Α and β should be as small as possible because they are probabilities of errors. Β = probability of a Type II error = P(Type II error) = probability of not rejecting the null hypothesis when the null hypothesis is false. Α = probability of a Type I error = P(Type I error) = probability of rejecting the null hypothesis when the null hypothesis is true. The decision is to reject H 0 when H 0 is false ( correct decision whose probability is called the Power of the Test).Įach of the errors occurs with a particular probability. The decision is not to reject H 0when, in fact, H 0 is false (incorrect decision known as a Type II error). The decision is to reject H 0 when H 0 is true (incorrect decision known as a Type I error). The four possible outcomes in the table are: The decision is not to reject H 0 when H 0 is true (correct decision). The outcomes are summarized in the following table: ![]() When you perform a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis H 0 and the decision to reject or not. Differentiate between Type I and Type II Errors. ![]()
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