What does it mean if research results are statistically significant?

Research results being statistically significant indicates that the observed effects or differences are unlikely to have occurred by chance alone. This means that the data provides sufficient evidence to suggest that there is a true effect or relationship present in the population being studied, rather than it being a random occurrence.

Statistical significance is often assessed using a p-value, which measures the probability of observing the obtained results if the null hypothesis (which states that there is no effect) were true. A p-value below a predetermined threshold (commonly 0.05) indicates that the likelihood of the results occurring due to random chance is low, thereby leading researchers to reject the null hypothesis and conclude that there is a significant effect.

In this context, the concept of statistical significance does not assert that the results are definitive or can be generalized across all contexts and populations without further evidence. Therefore, it is essential to interpret statistical significance in conjunction with other research factors, such as effect size and practical significance, to determine the broader implications of the findings. This contributes to a more nuanced understanding of the results beyond simply concluding they are "conclusive" or universally applicable.