You're reviewing an experiment on an Asana surface and the result is not statistically significant. The team wants to know whether that means there was truly no effect, or whether the test may simply have been underpowered.
How would you explain statistical power and false negatives in an experiment review?
How power relates to Type II errorWhy non-significant does not automatically mean no effectHow sample size and effect size drive experiment sensitivityHow to communicate underpowered results in a review