# What is Statistical Power and Why is it Important?

Statistical Power is the probability that a statistical test will detect differences when they truly exist.  Think of Statistical Power as having the statistical "muscle" to be able to detect differences between the groups you are studying, or making sure you do not "miss" finding differences.

In many efficacy studies we are looking at the differences between a treatment group (e.g., using a product) and a control group (e.g., not using a product).  If our treatment is truly different than the control we want to make sure that our statistical test will detect that difference.  This is where Statistical Power comes in.  We want to make sure that we have enough Statistical Power to ensure that we find the differences if they are there.

Statistical Power is determined by several factors, most importantly the size of the statistical significance selected, the size of the effect (amount of difference) we are expecting and the sample size.  Since we typically use significance levels of  .05 or .01 and we do not know the size of the effect in advance, we are often left with having to make decisions about sample size when planning a study to achieve sufficient Statistical Power. In short, we need to make sure that we have enough study participants to statistically detect the statistical differences observed.

Estimating Statistical Power and determining the appropriate sample size can get a bit tricky, and the mathematical details are beyond the scope of this article.  But, SEG Measurement can work with you to navigate this and other study design decisions at the outset of your study