College

Listed below are body temperatures from five different subjects measured at 8 AM and again at 12 AM. Find the values of [tex]$\overline{d}$[/tex] and [tex]$s_d$[/tex]. In general, what does [tex]$\mu_d$[/tex] represent?

[tex]
\[
\begin{array}{|c|c|c|c|c|c|}
\hline
\text{Temperature (} ^{\circ}F \text{) at 8 AM} & 98.2 & 99.1 & 97.3 & 97.6 & 97.4 \\
\hline
\text{Temperature (} ^{\circ}F \text{) at 12 AM} & 98.7 & 99.7 & 97.5 & 97.3 & 97.7 \\
\hline
\end{array}
\]
[/tex]

Let the temperature at 8 AM be the first sample, and the temperature at 12 AM be the second sample.

Find the values of [tex]$\overline{d}$[/tex] and [tex]$s_d$[/tex]:

- [tex]$\overline{d} = -0.26$[/tex] (Type an integer or a decimal. Do not round.)
- [tex]$s_d = \square$[/tex] (Round to two decimal places as needed.)

In general, [tex]$\mu_d$[/tex] represents the mean difference between the paired observations in the population.

Answer :

To solve the problem of finding [tex]\(\overline{d}\)[/tex] and [tex]\(s_d\)[/tex] for the listed body temperatures, follow these steps:

1. Identify the Paired Differences:
- We have temperatures for five subjects at 8 AM and 12 AM.
- Calculate the difference for each subject by subtracting the 8 AM temperature from the 12 AM temperature.

Differences:
- Subject 1: [tex]\(98.7 - 98.2 = 0.5\)[/tex]
- Subject 2: [tex]\(99.7 - 99.1 = 0.6\)[/tex]
- Subject 3: [tex]\(97.5 - 97.3 = 0.2\)[/tex]
- Subject 4: [tex]\(97.3 - 97.6 = -0.3\)[/tex]
- Subject 5: [tex]\(97.7 - 97.4 = 0.3\)[/tex]

2. Calculate the Mean of the Differences ([tex]\(\overline{d}\)[/tex]):
- Add up all the differences and divide by the number of subjects.

[tex]\[
\overline{d} = \frac{0.5 + 0.6 + 0.2 - 0.3 + 0.3}{5} = \frac{1.3}{5} = 0.26
\][/tex]

3. Calculate the Standard Deviation of the Differences ([tex]\(s_d\)[/tex]):
- First, find the squared differences from the mean for each subject.
- Then, find the average of these squared differences.
- Lastly, take the square root of the result to find [tex]\(s_d\)[/tex].

Squared Differences:
- Subject 1: [tex]\((0.5 - 0.26)^2 = 0.0576\)[/tex]
- Subject 2: [tex]\((0.6 - 0.26)^2 = 0.1156\)[/tex]
- Subject 3: [tex]\((0.2 - 0.26)^2 = 0.0036\)[/tex]
- Subject 4: [tex]\((-0.3 - 0.26)^2 = 0.3136\)[/tex]
- Subject 5: [tex]\((0.3 - 0.26)^2 = 0.0016\)[/tex]

Mean of Squared Differences:
[tex]\[
\text{Mean} = \frac{0.0576 + 0.1156 + 0.0036 + 0.3136 + 0.0016}{4} = \frac{0.492}{4} = 0.123
\][/tex]

[tex]\(s_d\)[/tex]:
[tex]\[
s_d = \sqrt{0.123} \approx 0.35
\][/tex]

Thus, the mean of the differences is [tex]\(\overline{d} = 0.26\)[/tex] and the standard deviation is [tex]\(s_d \approx 0.35\)[/tex].

4. Interpretation of [tex]\(\mu_{d}\)[/tex]:
- [tex]\(\mu_{d}\)[/tex] represents the mean population difference between the paired temperatures. It tells us about the average change or difference in temperatures at 8 AM and 12 AM across the entire population from which the samples were drawn.

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