What does the statistical significance level (alpha) indicate?

The statistical significance level, commonly denoted as alpha, serves as the threshold for determining whether the results of a statistical test can be considered statistically significant. Typically set at values like 0.05, 0.01, or 0.10, alpha represents the probability of rejecting the null hypothesis when it is actually true. When the p-value of a test falls below this alpha value, it indicates strong evidence against the null hypothesis, leading researchers to conclude that there is an effect or difference that is unlikely to be due to random chance.

In contrast, the other options refer to distinct statistical concepts. The average of a data set is a measure of central tendency, while the relationship between two variables often involves correlation or regression analysis, focusing on how two entities interact. Reliability of a data sample pertains to the consistency of measurement across samples, not directly tied to the significance level. Thus, the correct answer emphasizes the role of alpha as a benchmark for establishing significant findings in statistical hypothesis testing.