If a statistical test yields a significant result, what does it imply?

When a statistical test yields a significant result, it indicates that the observed data is unlikely to have occurred under the assumption that the null hypothesis is true. This rejection of the null hypothesis signifies that there is enough evidence to support an alternative hypothesis, suggesting that an effect or difference exists.

While it is true that a significant result may lead to important clinical implications and that sufficient power can also contribute to obtaining a significant result, these factors do not derive directly from the significance itself. Thus, the essence of a significant result is fundamentally connected to the rejection of the null hypothesis, making it the most precise interpretation of what a significant result entails.

Understanding the significance of a statistical result allows researchers and practitioners to make informed inferences about the data and its implications, which is crucial in fields like healthcare.