In research, a finding achieves a certain level of confidence when the observed effect is unlikely due to random chance alone. For example, if a new drug is tested and patients show improvement, the improvement is meaningful if the probability of it happening by chance is very low. This threshold is often set at 5% (a p-value of 0.05 or less), meaning there’s less than a 5% chance the observed outcome occurred randomly.
This concept is crucial for drawing reliable conclusions from data and making informed decisions. It helps researchers distinguish genuine effects from noise, ensuring that conclusions are based on evidence rather than chance occurrences. Historically, the development of statistical significance testing provided a more rigorous framework for scientific inquiry, moving beyond anecdotal observations and subjective interpretations. Its proper application reduces the risk of misleading findings and enhances the credibility of research.
