If a relationship between two variables is statistically significant, what does it indicate?

When a relationship between two variables is statistically significant, it suggests that there is an association between those variables in the population represented by the sample being studied. This means that the observed relationship is unlikely to be due to random chance alone. Statistical significance typically implies that the data provides strong enough evidence to reject the null hypothesis, which posits that no relationship exists.

In practical terms, this can be understood through p-values and confidence intervals. When researchers find a statistically significant result, it usually indicates that the p-value is below a predetermined threshold (commonly 0.05), implying that the likelihood of observing such a relationship due to random variation is very low. Consequently, the findings are generalized to suggest that a similar relationship likely exists in the broader population, making the correct response the one that affirms the relationship in the population represented by the sample.