Answer:
1) [tex]\bar X \pm ME[/tex]
And the margin of error for this case is [tex] ME= 5.4 [/tex]
And the confidence interval would be:
[tex] 61.5-5.4 = 56.1[/tex]
[tex] 61.5+5.4 = 66.9[/tex]
2) For this case the best estimator for the population mean [tex]\mu [/tex] is given by the sample mean:
[tex]\bar X = 61.5[/tex]
And the reason of this is beacuse is an unbiased estimator of the parameter:
[tex] E(\bar X) = \mu[/tex]
Step-by-step explanation:
Data given:
53.1, 60.2, 60.6, 62.1, 64.4, 68.6.
We can calculate the sample mean with the following formula:
[tex]\bar X = \frac{\sum_{i=1}^n X_i}{n}[/tex]
[tex]\bar X= 61.5[/tex] represent the sample mean for the sample
[tex]\mu[/tex] population mean (variable of interest)
s represent the sample standard deviation
n represent the sample size
Part 1
The confidence interval for the mean is given by the following formula:
[tex]\bar X \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex] (1)
Or equivalently:
[tex]\bar X \pm ME[/tex]
And the margin of error for this case is [tex] ME= 5.4 [/tex]
And the confidence interval would be:
[tex] 61.5-5.4 = 56.1[/tex]
[tex] 61.5+5.4 = 66.9[/tex]
Part 2
For this case the best estimator for the population mean [tex]\mu [/tex] is given by the sample mean:
[tex]\bar X = 61.5[/tex]
And the reason of this is beacuse is an unbiased estimator of the parameter:
[tex] E(\bar X) = \mu[/tex]