Why is a p-value of 0.05 significant in research?

A p-value of 0.05 is significant in research because it indicates that there is a 95% confidence level in the results obtained from a statistical test. This means that if the null hypothesis were true, there is only a 5% probability of observing the results (or something more extreme) due to random chance alone. Researchers often use this threshold to determine whether to reject the null hypothesis, thereby supporting the alternative hypothesis. A p-value below 0.05 suggests that the observed data is unlikely to occur under the null hypothesis, leading to the conclusion that an effect or relationship likely exists.

This interpretation stems from the foundational principles of hypothesis testing, where a p-value is used as a measure of the strength of evidence against the null hypothesis. A p-value at or below 0.05 generally indicates sufficient evidence to consider the finding statistically significant, which is a critical aspect of interpreting research findings.