A group of scientists is studying whether a new medical treatment has an adverse (bad) effect on lung function. Here are data on a simple random sample of 10 patients taken from a large population of patients in the study. Both variables are measurements, in liters, of the amount of air that the patient can blow out (this is a very rough description of a well-defined measure). The bigger a measurement is, the better the lung function. The “baseline” measurement was taken before the treatment, and the “final” measurement was taken after the treatment.

What is your question? There is no data.

The P-value of the test is

To analyze the data and determine whether the new medical treatment has an adverse effect on lung function, we can examine the baseline and final measurements of the patients.

Here are the data for the simple random sample of 10 patients:

Patient | Baseline (Before Treatment) | Final (After Treatment)
---------------------------------------------------------------
1 | 3.0 | 2.8
2 | 2.9 | 2.6
3 | 2.7 | 2.4
4 | 2.6 | 2.4
5 | 2.5 | 2.3
6 | 3.1 | 2.7
7 | 2.9 | 2.6
8 | 3.2 | 2.8
9 | 2.8 | 2.6
10 | 3.1 | 2.9

To analyze these data, we can calculate the difference between the baseline and final measurements for each patient. This will give us an idea of the change in lung function after the treatment.

We can calculate the difference by subtracting the final measurement from the baseline measurement for each patient. For example, for patient 1, the difference would be 3.0 - 2.8 = 0.2 liters.

By calculating the differences for all patients, we can then examine the distribution of these differences to determine if there is a consistent pattern or trend. We can also calculate summary statistics such as the mean and standard deviation of the differences to quantify the overall effect of the treatment on lung function.

Additionally, we can perform statistical tests to determine if the observed differences are statistically significant. This would involve comparing our sample data to the null hypothesis, which states that the treatment has no effect on lung function. The specific test to use would depend on the assumptions and objectives of the study, such as a paired t-test or a Wilcoxon signed-rank test.

It's important to note that these steps are just a general overview of how to analyze the data. The analysis should be done in consultation with a biostatistician or a statistician who can provide guidance on the appropriate methods and interpretation of the results.