Answer:
(a) 95% confidence interval for the population mean is [76.2 , 83.8].
(b) 95% confidence interval for the population mean after change in sample size is [77.32 , 82.68].
(c) The effect of a larger sample size on the margin of error is that the margin of error will increase.
Step-by-step explanation:
We are given a simple random sample of 60 items resulted in a sample mean of 80. The population standard deviation is σ = 15.
(a) Firstly, the pivotal quantity for 95% confidence interval for the population mean is given by;
P.Q. =
~ N(0,1)
where,
= sample mean = 80
= population standard deviation = 15
n = sample of items = 60
= population mean
<em>Here for constructing 95% confidence interval we have used One-sample z test statistics as we know about the population standard deviation.</em>
<u>So, 95% confidence interval for the population mean, </u>
<u> is ;</u>
P(-1.96 < N(0,1) < 1.96) = 0.95 {As the critical value of z at 2.5% level
of significance are -1.96 & 1.96}
P(-1.96 <
< 1.96) = 0.95
P(
<
<
) = 0.95
P(
<
<
) = 0.95
<u>95% confidence interval for</u>
= [
,
]
= [
,
]
= [76.2 , 83.8]
Therefore, 95% confidence interval for the population mean is [76.2 , 83.8].
(b) Now, the sample size has been changed to 120 items.
So, <u>95% confidence interval for</u>
= [
,
]
= [
,
]
= [77.32 , 82.68]
Therefore, 95% confidence interval for the population mean after change in sample size is [77.32 , 82.68].
(c) The effect of a larger sample size on the margin of error is that the margin of error will increase that's why the confidence interval in part (b) is narrower than part (a).