>Statistical significance is bullshit. Learning about it is as useful as learning about phlogiston.
The term-of-art "statistical significance" isn't bs because we ultimately have to choose what to pay attention to. Removing "statistical significance" from the vocabulary doesn't change the underlying reality about people deciding what to do based on a threshold of a number.
The observed effect of <something> is either:
(1) appearance of cause & effect is actually not there and just random chance or coincidence
That's true but the abuses still doesn't eliminate the need to name the concept of real cause & effect vs random chance. Whatever alternative mental framework one uses to decide which of those scenarios is happening, you will arrive at something that looks like "statistical significance" even if you don't call it that.
As an analogy, even though "averages" in math is misused, it doesn't mean "averages are bs".
Sorry, but statistical significance has a pretty narrow meaning, and it's wrong.
> Removing "statistical significance" from the vocabulary doesn't change the underlying reality about people deciding what to do based on a threshold of a number.
I'm not arguing to remove it from the vocabulary. I'm arguing that that bloomin' threshold is the source of many problems.
The article also isn't about methodology, it's about the secondary school curriculum. To provide pupils with a false understanding of statistics is just bad. And to teach them why it's bad, is hard.
The term-of-art "statistical significance" isn't bs because we ultimately have to choose what to pay attention to. Removing "statistical significance" from the vocabulary doesn't change the underlying reality about people deciding what to do based on a threshold of a number.
The observed effect of <something> is either:
(1) appearance of cause & effect is actually not there and just random chance or coincidence
(2) a real cause & effect and not random chance
Yes.. but "statistical significance" leads to "p-hacking" and other academic fraud! (https://en.wikipedia.org/wiki/Data_dredging)
That's true but the abuses still doesn't eliminate the need to name the concept of real cause & effect vs random chance. Whatever alternative mental framework one uses to decide which of those scenarios is happening, you will arrive at something that looks like "statistical significance" even if you don't call it that.
As an analogy, even though "averages" in math is misused, it doesn't mean "averages are bs".