A medical study is conducted to determine which migraine treatment, A or B, provides faster relief. The study uses 10 volunteers who claim to suffer from migraines. Half of the volunteers are randomly assigned to use treatment A when they experience their first migraine. The other half are assigned to use treatment B. Then, after no treatment for one month, the treatments are reversed. The volunteers each record the amount of time it takes, in minutes, to experience relief from their migraine under each treatment. The data are displayed in the table, and a dot plot of the differences is given.

\begin{tabular}{|l|c|c|c|c|c|c|c|c|c|c|}
\hline Volunteer & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 & 10 \\
\hline Treatment A & 10 & 13 & 13 & 9 & 13 & 12 & 14 & 10 & 8 & 7 \\
\hline Treatment B & 19 & 18 & 19 & 15 & 20 & 16 & 16 & 16 & 13 & 17 \\
\hline Difference [tex]$(A - B)$[/tex] & -9 & -5 & -6 & -6 & -7 & -4 & -2 & -6 & -5 & -10 \\
\hline
\end{tabular}

Difference [tex]$(A - B)$[/tex] in time to experience relief (min)

The researchers would like to construct a [tex]$99 \%$[/tex] confidence interval for the mean difference [tex]$(A - B)$[/tex] in the time it took to experience relief. Formulate the necessary information for this calculation.



Answer :

To construct a 99% confidence interval for the mean difference in the time it takes to experience relief using treatments A and B, we'll follow these steps:

1. Calculate the mean of the differences:

The differences recorded from the experiment are:
[tex]\(-9, -5, -6, -6, -7, -4, -2, -6, -5, -10\)[/tex].

The mean ([tex]\(\bar{d}\)[/tex]) is the sum of these differences divided by the number of differences (n = 10):
[tex]\[ \bar{d} = \frac{1}{n} \sum_{i=1}^{n} d_i = \frac{-9 + (-5) + (-6) + (-6) + (-7) + (-4) + (-2) + (-6) + (-5) + (-10)}{10} = \frac{-60}{10} = -6 \][/tex]

2. Calculate the standard deviation of the differences:

To find the sample standard deviation ([tex]\(s\)[/tex]), you use the formula:
[tex]\[ s = \sqrt{\frac{1}{n - 1} \sum_{i=1}^{n} (d_i - \bar{d})^2} \][/tex]
For our data, the value of the standard deviation is:
[tex]\[ s \approx 2.309 \][/tex]

3. Determine the critical value for the 99% confidence interval:

With a 99% confidence interval, the significance level ([tex]\(\alpha\)[/tex]) is 0.01. Since we're interested in a two-tailed test, we split [tex]\(\alpha\)[/tex] into two: [tex]\(\alpha/2 = 0.005\)[/tex]. Given that our sample size is [tex]\(n = 10\)[/tex], the degrees of freedom (df) are [tex]\(n - 1 = 9\)[/tex].

The critical value ([tex]\(t^\ast\)[/tex]) can be found using a t-distribution table or statistical software for [tex]\(df = 9\)[/tex] and [tex]\(\alpha/2 = 0.005\)[/tex]:
[tex]\[ t^\ast \approx 3.250 \][/tex]

4. Calculate the standard error of the mean difference:

The standard error of the mean difference ([tex]\(\text{SE}_\bar{d}\)[/tex]) is calculated as:
[tex]\[ \text{SE}_\bar{d} = \frac{s}{\sqrt{n}} = \frac{2.309}{\sqrt{10}} \approx 0.730 \][/tex]

5. Calculate the margin of error:

The margin of error (MOE) is calculated by multiplying the critical value by the standard error:
[tex]\[ \text{MOE} = t^\ast \times \text{SE}_\bar{d} = 3.250 \times 0.730 \approx 2.373 \][/tex]

6. Construct the confidence interval:

Finally, the 99% confidence interval for the mean difference is constructed by adding and subtracting the margin of error from the sample mean:
[tex]\[ \bar{d} \pm \text{MOE} = -6 \pm 2.373 \][/tex]

So, the confidence interval is:
[tex]\[ (-8.373, -3.627) \][/tex]

### Conclusion
Based on our calculations, the 99% confidence interval for the mean difference in relief time between treatments A and B is approximately [tex]\( (-8.373, -3.627) \)[/tex]. This interval suggests that, on average, treatment A provides relief between approximately 3.63 and 8.37 minutes faster than treatment B for the volunteers in this study.