What does the term "statistically significant" imply about study results?

The term "statistically significant" indicates that the results of a study are unlikely to have occurred due to random chance or error. This means that the findings have reached a level of statistical reliability that suggests the observed effects or differences are real and not just products of random variability. When the results are statistically significant, researchers can be more confident in drawing conclusions based on the data and can consider them as evidence supporting the hypotheses being tested.

For instance, if a study finds a statistically significant difference in health outcomes between two treatment groups, it implies that this difference is meaningful and not just a fluke that could arise if the study were repeated multiple times with different samples.

In contrast, while a significant effect on the subject may be true for some findings, statistical significance specifically does not directly assert the significance of the effect in practical or clinical terms. Adequate sample size is important for achieving statistical significance but does not automatically imply that the results are statistically significant; a smaller sample could yield statistically significant results if the effect is large enough. Lastly, while further investigation can be prudent in light of significant results, statistical significance itself does not inherently necessitate further inquiry. Thus, the implication of study results being statistically significant primarily relates to their reliability in confirming a real