Respuesta :
Answer:
a) [tex]\bar d= \frac{\sum_{i=1}^n d_i}{n}= \frac{361}{5}=72.2[/tex]
[tex]s_d =\frac{\sum_{i=1}^n (d_i -\bar d)^2}{n-1} =9.311[/tex]
b) [tex]63.331 < \mu_{left arm}-\mu_{right arm} <81.069[/tex]
Step-by-step explanation:
Previous concepts
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".
The margin of error is the range of values below and above the sample statistic in a confidence interval.
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
Solution
Let put some notation
x=value for right arm , y = value for left arm
x: 102, 101,94,79,79
y: 175,169,182,146,144
The first step is calculate the difference [tex]d_i=y_i-x_i[/tex] and we obtain this:
d: 73, 68, 88, 67, 65
Part a
The second step is calculate the mean difference
[tex]\bar d= \frac{\sum_{i=1}^n d_i}{n}= \frac{361}{5}=72.2[/tex]
The third step would be calculate the standard deviation for the differences, and we got:
[tex]s_d =\frac{\sum_{i=1}^n (d_i -\bar d)^2}{n-1} =9.311[/tex]
Part b
The next step is calculate the degrees of freedom given by:
[tex]df=n-1=5-1=4[/tex]
Now we need to calculate the critical value on the t distribution with 4 degrees of freedom. The value of [tex]\alpha=1-0.9=0.1[/tex] and [tex]\alpha/2=0.05[/tex], so we need a quantile that accumulates on each tail of the t distribution 0.05 of the area.
We can use the following excel code to find it:"=T.INV(0.05;4)" or "=T.INV(1-0.05;4)". And we got [tex]t_{\alpha/2}=\pm 2.13[/tex]
The confidence interval for the mean is given by the following formula:
[tex]\bar d \pm t_{\alpha/2}\frac{s}{\sqrt{n}}[/tex] (1)
Now we have everything in order to replace into formula (1):
[tex]72.2-2.13\frac{9.311}{\sqrt{5}}=63.331[/tex]
[tex]72.2+2.13\frac{9.311}{\sqrt{5}}=81.069[/tex]
So on this case the 90% confidence interval would be given by (63.331;81.069).
[tex]63.331 < \mu_{left arm}-\mu_{right arm} <81.069[/tex]