What does the term "statistical significance" imply?

The term "statistical significance" indicates that the observed results in a dataset are credible and unlikely to have occurred due to random chance. When researchers determine that results are statistically significant, it typically means that the probability of obtaining those results if there were no real effect (i.e., if the null hypothesis were true) is very low. This low probability, often represented by a p-value of less than a specified threshold (commonly 0.05), lends strong support to the conclusion that the observed effects are real and not just random variations in the data.

In practical terms, statistical significance helps researchers understand whether their findings can be trusted and whether they reflect true relationships or differences within the population being studied. This credibility is essential when making conclusions based on data, guiding decision-making, and forming hypotheses for further research.