Question: It is important to understand that hypothesis test rely on sample statistics in order to make assertion about the null hypothesis Ho; the scenario of

 It is important to understand that hypothesis test rely on samplestatistics in order to make assertion about the null hypothesis Ho; thescenario of status quo; the "do nothing"scenario; the scenario of equality. Similar

It is important to understand that hypothesis test rely on sample statistics in order to make assertion about the null hypothesis Ho; the scenario of status quo; the "do nothing"scenario; the scenario of equality. Similar to the condence interval, there are margins of error we need be aware of. In hypothesis testing these are known as Type | Error and Type II Error. We use the sample data to test the possibility H0 might be true against the claim of Ha. Worksheet After this lesson you should nish working on Worksheet21 Book Resource In order to better understand the subject matter you are encourage to read Chapter 9.2 in the book. Denition Type | Error: The decision is to reject H0 when H0 is true a = P(Type I error) = probability of rejecting the null hypothesis when the null hypothesis is true. Type II Error: The decision is not to reject H0 when, in fact, H0 is false Denition Type | Error: The decision is to reject H0 when H0 is true a = P(Type I error) = probability of rejecting the null hypothesis when the null hypothesis is true. Type II Error: The decision is not to reject H0 when, in fact, H0 is false [3 = P(Type || error) = probability of not rejecting the null hypothesis when the null hypothesis is false. Example Suppose the null hypothesis is, H0: Frank's rock climbing equipment is safe. Type I error: Reject true H0, meaning reject the fact the equipment is safe. Potential danger is that Frank does not take the safe equipment with him and thereby adds unnecessary risk to his climbing expedition. Type II error: Fail to reject false H0, meaning fail to reject the fact that the equipment is not safe. Potential danger is that Frank relies on a rock climbing equipment that is not safe. Thus putting hineWh he is [3 = P(Type ll error) = probability of not rejecting the null hypothesis when the null hypothesis is false. Example Suppose the null hypothesis is, H0: Frank's rock climbing equipment is safe. Type I error: Reject true H0, meaning reject the fact the equipment is safe. Potential danger is that Frank does not take the safe equipment with him and thereby adds unnecessary risk to his climbing expedition. Type II error: Fail to reject false H0, meaning fail to reject the fact that the equipment is not safe. Potential danger is that Frank relies on a rock climbing equipment that is not safe. Thus putting himself in danger, of which he is unaware. a = Probability that Frank rejects that the equipment is safe, even though it is. B = Probability that Frank does not reject that the equipment is not safe, even though it isn't

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