What is the difference between statistical and practical significance?

What is the difference between statistical and practical significance?

Statistical significance refers to the likelihood that a result or relationship is caused by something other than mere random chance. Practical significance, on the other hand, considers whether the size of the effect is large enough to be of real-world relevance.

Can you give me an example of each?

Sure! For statistical significance, if a study finds a p-value of 0.01, it suggests a strong likelihood that the result is not due to chance. For practical significance, if a new drug lowers blood pressure by 1 mmHg, it may be statistically significant but not practically significant if that change doesn't lead to meaningful health improvements.

Why is it important to understand both?

Understanding both is crucial because a result can be statistically significant but not practically useful. This helps researchers and practitioners make informed decisions based on both the data and its real-world implications.

How can I determine practical significance in my research?

To determine practical significance, consider the effect size, the context of the research, and whether the results lead to actionable insights or improvements in practice.