At an alpha level of 0.05, what percentage represents the threshold for rejecting results?

In statistical hypothesis testing, the alpha level, often denoted as α, is the threshold for determining whether to reject the null hypothesis. An alpha level of 0.05 signifies a 5% risk of concluding that a difference exists when there is no actual difference (a Type I error).

When researchers set their alpha level at 0.05, they are indicating that they are willing to accept a 5% probability for making this erroneous rejection. Thus, the remaining percentage relates to the certainty with which results can be declared statistically significant. In this context, the threshold for rejecting the null hypothesis is determined by the cumulative probability. Since an alpha level of 0.05 represents the threshold for significance, the complementary percentage of 95% represents the threshold of confidence with which researchers reject the null hypothesis, meaning they are 95% certain that the results observed are not due to random chance.

This understanding of the alpha level provides a foundational concept in hypothesis testing and helps in interpreting statistical results effectively, particularly in the field of healthcare statistics where determining the efficacy and safety of treatments is crucial.