How to Interpret Statistically Insignificant Results?
Statistically insignificant results should not be dismissed outright. They can provide valuable information about the absence of an effect or the need for further investigation. Researchers should consider the following:
Confidence intervals: Examine the range within which the true effect size is likely to lie. Effect size: Consider the magnitude of the observed effect, even if it is not statistically significant. Replication: Seek additional studies to confirm or refute the findings. Meta-analysis: Combine results from multiple studies to increase the overall power.
