When we conduct a hypothesis test, there are two ways to make a mistake. The null hypothesis might be correct, and we end up rejecting it. This is called a Type I error. On the other hand, the null hypothesis might be false, and we fail to reject it. This is called a Type II error. Either type of error can be costly, though not necessarily equally costly. In the following two scenarios, think about what is the alternative hypothesis? In plain language, state each type of error Whom does each error harm? Which type of error has the costliest consequence? A) Suppose the null hypothesis, Ho, is: The victim of an automobile accident is alive when he arrives at the emergency room of a hospital. B) Suppose the null hypothesis, Ho, is: Frank's rock climbing equipment is safe.
scenerio 1
Ho, is: The victim of an automobile accident is alive when he arrives at the emergency room of a hospital.
H1: victim is dead when he arrives
type 1 error : the victim is alive but considered dead at arrival in emergency room
type 2 error: the victim is dead but taken not considered dead at arrival
type 1 error is costliest as victim is considered dead although he is alive ...this might lead to loss of a life when chances were there to save him
Scenerio 2
Ho, is: Frank's rock climbing equipment is safe.
H1: climbing equipment is not safe.
type 1 error : equipment is safe but not considered safe
type 2 error: equipment is not safe but considered safe
type 2 error is costliest as frank has chances of more prone to accident
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