Respuesta :
Answer:
Consider the following explanation
Step-by-step explanation:
Part 1
Confidence interval for Population mean is given as below:
Confidence interval = Xbar ± Z*σ/sqrt(n)
We are given
Confidence level = 95%
Critical Z value = 1.96
(by using z-table)
Xbar = 200.318
σ = 10.721
n = 148
Lower limit = Xbar - Z*σ/sqrt(n)
Lower limit = 200.318 – 1.96*10.721/sqrt(148)
Lower limit = 200.318 – 1.7272
Lower limit = 198.591
Part 2
Confidence interval for Population mean is given as below:
Confidence interval = Xbar ± Z*σ/sqrt(n)
We are given
Confidence level = 95%
Critical Z value = 1.96
(by using z-table)
Xbar = 200.318
σ = 10.721
n = 148
Upper limit = Xbar + Z*σ/sqrt(n)
Upper limit = 200.318 + 1.96*10.721/sqrt(148)
Upper limit = 200.318 + 1.7272
Upper limit = 202.045
Part 3
Confidence interval for Population mean is given as below:
Confidence interval = Xbar ± Z*σ/sqrt(n)
We are given
Confidence level = 95%
Critical Z value = 1.96
(by using z-table)
Xbar = 196.085
σ = 12.372
n = 164
Lower limit = Xbar - Z*σ/sqrt(n)
Lower limit = 196.085 – 1.96*12.372/sqrt(164)
Lower limit = 196.085 – 1.8935
Lower limit = 194.191
Part 4
Confidence interval for Population mean is given as below:
Confidence interval = Xbar ± Z*σ/sqrt(n)
We are given
Confidence level = 95%
Critical Z value = 1.96
(by using z-table)
Xbar = 196.085
σ = 12.372
n = 164
Upper limit = Xbar + Z*σ/sqrt(n)
Upper limit = 196.085 + 1.96*12.372/sqrt(164)
Upper limit = 196.085 + 1.8935
Upper limit = 197.979
Part 5
Confidence interval for difference is given as below:
Confidence interval = (X1bar – X2bar) ± Z* sqrt[(σ12 / n1)+(σ22 / n2)]
We are given
Confidence level = 95%
Critical Z value = 1.96
(by using z-table)
Confidence interval = (X1bar – X2bar) ± Z* sqrt[(σ12 / n1)+(σ22 / n2)]
Confidence interval = (200.318 – 196.085) ± 1.96* sqrt[(10.721^2 / 148)+( 12.372^2 / 164)]
Confidence interval = 4.233 ± 1.96* 1.3077
Confidence interval = 4.233 ± 2.563092
Lower limit = 4.233 - 2.563092 = 1.669908
Upper limit = 4.233 + 2.563092 = 6.796092
Confidence interval = (1.670, 6.796)