Answer:
The p-value is the probability of getting a test statistic at least as extreme as the one representing the sample data, assuming that the null hypothesis is true.
Explanation:
The p-value is well-defined as per the probability, [under the null hypothesis (H₀)], of attaining a result equivalent to or more extreme than what was the truly observed value of the test statistic.
A small p-value (typically ≤ 0.05) specifies solid proof against the null hypothesis (H₀), so you discard H₀. A large p-value (> 0.05) specifies fragile proof against the H₀, so you fail to discard H₀.
The complete sentence is:
The p-value is the probability of getting a test statistic at least as extreme as the one representing the sample data, assuming that the null hypothesis is true.