Which of the following is the correct interpretation of the p-value? A. The p-value is the probability of getting a test statistic equal to or more extreme than the sample result if there is no difference in the mean number of partners. B. The p-value is the probability of getting a test statistic equal to or more extreme than the sample result if there is a difference in the mean number of partners. C. The p-value is the probability of getting a test statistic equal to or more extreme than the sample result if there is no difference in the sample mean number of partners. D. The p-value is the probability of getting a test statistic equal to or more extreme than the sample result if there is a difference in the sample mean number of partners.

The correct option is (A).

Step-by-step explanation:

The p-value is well defined as the probability, [under the null hypothesis (H₀) ], of attaining a result equivalent to or more extreme than what was truly observed.

From the provided options we can guess that the hypothesis was defined as follows:

H₀: There is no difference in the mean number of partners, i. e. μ₁ - μ₂ = 0.

Hₐ: There is difference in the mean number of partners, i. e. μ₁ - μ₂ ≠ 0.

The test is two tailed mean difference test.

A z-test or a t-test can be used to conclude the result.

In this case the p-value can be defined as the probability of obtaining a test statistic value equal to or more extreme that the results obtained from the sample, when the difference between the mean number of partners is 0.

Thus, the correct interpretation of the p-value is provided by statement (A).