Respuesta :
Answer:
(a) Yes, there is evidence that the water temperature is acceptable at [tex]\alpha = 0.05[/tex] (b) 0.9987 (c) 6.647274e-06
Step-by-step explanation:
Let X be the random variable that represents the water temperature. The water temperature has been measured on n = 9 randomly chosen days (a small sample), the sample average temperature is [tex]\bar{x}[/tex] = 100°F and [tex]\sigma[/tex] = 2°F. We suppose that X is normally distributed.
We have the following null and alternative hypothesis
[tex]H_{0}: \mu = 102[/tex] vs [tex]H_{1}: \mu > 102[/tex] (upper-tail alternative)
We will use the test statistic
[tex]Z = \frac{\bar{X}-102}{2/\sqrt{9}}[/tex] and the observed value is
[tex]z_{0} = \frac{100-102}{2/\sqrt{9}} = -3[/tex].
(a) The rejection region is given by RR = {z | z > 1.6448} where 1.6448 is the 95th quantile of the standard normal distribution. Because the observed value -3 does not belong to RR, we fail to reject the null hypothesis. In other words, there is evidence that the water temperature is acceptable at [tex]\alpha = 0.05[/tex].
(b) The p-value for this test is given by P(Z > -3) = 0.9987
(c) P(Accepting [tex]H_{0}[/tex] when [tex]\mu = 106[/tex]) = P(The observed value is not in RR when [tex]\mu = 106[/tex]) = P([tex]\frac{\bar{X}-102}{2/\sqrt{9}}[/tex] < 1.6448 when [tex]\mu = 106[/tex]) = P([tex]\bar{X}[/tex] < 102 + (1.6448)([tex]2/\sqrt{9}[/tex]) when [tex]\mu = 106[/tex]) = P([tex]\bar{X}[/tex] < 103.0965) when [tex]\mu = 106[/tex]) = P([tex](\bar{X}-106)/(2/\sqrt{9}) < (103.0965-106)/(2/\sqrt{9})[/tex])) = P(Z < -4.3552) = 6.647274e-06