In statistics a power gives reference to the likelihood of a hypothesis test it helps to detect an effect if there legitimately is one. A test which is more substantial in terms of statistic test inclines more towards rejecting a (Type II error) which is a false negative.
It is important to ensure power that is enough in your study because in case you do not ensure enough power in your studies you would not be able to identify a result that is statistically significant even if there is practical significance all of the study you have done would futile because it would lack reasonability to answer the research questions you asked.
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