Question

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.

Answer #1

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

1. Suppose that null hypothesis, H0, is: Frank’s rock climbing
equipment is safe. State the Type I and Type II error.
2. Suppose that the null hypothesis, H0, is: The victim of an
automobile accident is alive when he arrives at the emergency room
of a hospital. State the Type I and Type II error.
3. The p-value for a hypothesis test is 0.07. Decide whether the
null hypothesis should be rejected at (a) α = 0.05, (b) α =...

Conduct a test of the null hypothesis that the mean height for
all students in the Census at School database is equal to 155 cm vs
the alternative that the mean Height is greater than 155 cm. Use a
significance level of 0.05.
a. State the null and alternative hypotheses.
Ho: m = 155
Ha: m > 155
b. Provide the Statcrunch output table.
Hypothesis test results:
Variable
Sample Mean
Std. Err.
DF
T-Stat
P-value
Height
159.86
1.7311103
49
2.8074468...

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