Respuesta :
Answer:
(a) The null hypothesis will be rejected.
(b) Type I error
(c) The null hypothesis will not be rejected. The error is type II error.
Step-by-step explanation:
The hypothesis provided is:
[tex]H_{0}: \mu = 0\\ H_{a} : \mu > 0[/tex]
The p-value of the test obtained is 0.03
(a)
Decision rule for hypothesis testing, based on p-value, states that if the p-value is less than the significance level (α) then the null hypothesis is rejected and vice versa.
The significance level is α = 0.10
Then,
[tex]p-value = 0.03 < \alpha = 0.10[/tex]
Thus, the null hypothesis will be rejected.
Conclusion:
The null hypothesis is rejected stating that the value of μ is more than 0.
(b)
If the decision in (a) is an error, i.e. the null hypothesis is rejected when in fact it is true, this type of error is known as type I error.
(c)
The significance level is α = 0.01
Then,
[tex]p-value = 0.03 > \alpha = 0.01[/tex]
Thus, the null hypothesis will not be rejected.
Conclusion:
The null hypothesis was not rejected stating that the value of μ is 0.
If this decision is an error, i.e. the null hypothesis was not rejected when in fact it is false, this type of error is known as type II error.
