Steve Tippins warns that statistical significance with large samples can make trivial effects look important. He argues researchers should focus on practical significance instead, grounding findings in real costs, actual thresholds, and what stakeholders actually care about.
If you have a large sample with little variability, I can still find microscopic events or effects. May not be what you want to be reporting. Your practical significance should be tied to things like cost-benefit, real-world thresholds, stakeholder interests, and is it meaningful change, not just change. I knew a school once that once said, "Well, we want to have all of our students talk about social change," and what they meant was social change for good, but they did They didn't say that when they first started this process, so social change could have been interpreted as, "Yeah, I want horrible social change." They evolved over time to realize they had done limited what they were going to get or were going to get things they didn't want, so they now— social change for good became part of their shtick. Drop the word "help" in the comments and I'll send you the link for my free dissertation help community.
