What does a p-value of less than 0.05 indicate?

A p-value of less than 0.05 indicates that there is less than a 5% probability that the observed results would occur under the null hypothesis. In hypothesis testing, the null hypothesis generally represents a statement of no effect or no difference. When researchers set a significance level, often at 0.05, they are establishing a threshold to help determine whether to reject the null hypothesis. A p-value below this threshold suggests that the evidence against the null hypothesis is strong enough to consider that the effect observed is likely not due to random chance.

The interpretation of a p-value under 0.05 implies that the data collected provides statistically significant evidence in favor of the alternative hypothesis, which posits that there is an effect or a difference. Therefore, this is important for researchers who want to establish the validity and reliability of their findings within a statistical framework.

Understanding the significance level and interpreting p-values correctly is fundamental in statistics and biomedical engineering, as it helps researchers make informed decisions based on empirical evidence.