What is the difference between statistically significant evidence and clinically significant evidence?

Original Discussion Question: What is the difference between statistically significant evidence and clinically significant evidence? How would each of these findings be used to advance an evidenced-based practice project? Answer by another student: Statistical significance is the association or difference exists between the variables that weren’t caused solely by normal variation or chance. It is dependent on the study’s sample size; with “large sample sizes, even small treatment effects (which are clinically inconsequential) can appear statistically significant; therefore, the reader has to interpret carefully whether this “significance” is clinically meaningful”. Researchers use statistics to answer the questions of probability. This leads to the determination if a hypothesis will be accepted or rejected. Statistical significance “only addresses a hypothesis about whether or not differences exist, statistically, between groups” (Page, 2014). Clinically significant results are dependent on its implications on existing practice-treatment effect size being one of the most important factors that drives treatment decisions. Clinically significant should reflect the extent of changes, if the changes make a difference in patient lives, how long the effects last, acceptability by the consumer, cost effectiveness and the ease of implementation (Page, 2014).