Respuesta :
Answer:
(a) Test statistics = -4.54
(b) P-value = 1.9999
(c) We conclude that the population mean is equal to 17.
(d) Critical values for the test statistic are -1.96 and 1.96 .
(e) Test statistics is less than -1.96 or more than 1.96 represent the rejection region.
Step-by-step explanation:
We are given that ;
Null Hypothesis, [tex]H_0[/tex] : [tex]\mu[/tex] = 17 where, [tex]\mu[/tex] = population mean
Alternate Hypothesis, [tex]H_1[/tex] : [tex]\mu \neq[/tex] 17
Also, a sample of 40 provided a sample mean of 14.13 and the population standard deviation is 4 i.e.;
[tex]Xbar[/tex] = 14.13 [tex]\sigma[/tex] = 4 and n = 40
(a) The test statistics used here will be;
[tex]\frac{Xbar - \mu}{\frac{\sigma}{\sqrt{n} } }[/tex] ~ N(0,1)
Test statistics = [tex]\frac{14.13 - 17}{\frac{4}{\sqrt{40} } }[/tex] = -4.54
(b) P-value = P(Z > -4.54) = P(Z < 4.54) = 1 - P(Z >= 4.54)
From seeing the z % table we observe that the p-value will be less than 0.99995 in one -tail but in two tail case it will be less than 1.9999 .
(c) At 5% level of significance, we will accept null hypothesis because p -value is more than the significance level so we conclude that population mean is equal to 17.
(d) Using significance level of 5%, the critical values for the test statistic are -1.96 and 1.96 .
(e) If our test statistics is less than -1.96 or more than 1.96, then it will lie in the rejection region and we reject null hypothesis.
And since our test statistics is less than -1.96, so we reject [tex]H_0[/tex] and conclude that population mean is not equal to 17.