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).

WHAT IS THE DIFFERENCE BETWEEN STATISTICALLY SIGNIFICANT EVIDENCE AND CLINICALLY SIGNIFICANT EVIDENCE?

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