What exactly does it mean when a result is statistically significant vs. insignificant? When we compare, for example, a t-stat and the critical t-value, I know we either reject or fail to reject the null hypothesis based on whether the t-stat is less than or greater than the t-value. What exactly does it mean when the t-stat is greater than the critical t-value? What even is the “t-stat” and “critical t-value” in layman terms?
After doing enough problems, I’m sure I’ll get it, but I don’t like _not_ being able to explain this to myself simply – which indicates that I haven’t understood it well enough. Can someone please dumb all of this down for me and truly explain it to me like I’m a child?
In: Mathematics
It’s a really bad term used colloquially.
Okay, in statistics we have a p value. This basically means the percent chance that what you thought were results that confirmed your hypothesis are actually the results you’d get even if your hypothesis were completely wrong (the null hypothesis). Normally .05, or 5%, is the number used to reject the null hypothesis, to claim “statistically significant.”
Unfortunately, the term is abused to say “We were right!” No, it doesn’t mean that. It just means there’s a less than 5% chance you were completely wrong. P can be set at any number, and studies do go lower than .05. There are many more things about a study that can give you confidence, or take it away, than the p value.
In fact, there’s a thing called p-hacking, which means massaging the data to get that P value down below .05 although your hypothesis really is rubbish, crafted to get the answer you want.
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