17/04/2026
Just because you observe something doesn’t mean that is the truth. And just because you don’t observe it doesn’t mean it is not true.
Imagine setting a trap 5 times, and someone steals 4 out of those 5 times. Logically, you might conclude that the person is a thief.
But statistics will pause and say: "We don't have enough evidence yet to call him a thief."
It may sound strange, but statistically, it makes sense.
Statistics reasons like this: "stealing 4 out of 5 times could still happen by chance. Concluding too quickly might lead to a wrong decision."🤔
That's how we reason in statistics; we always want to minimize errors in judgment. We always avoid concluding that something is true when it is actually false and avoid rejecting something that is actually true
This is exactly why we always tell students to stop saying "accept H₀" instead, we recommend saying "fail to reject or do not reject H₀"
Because we are cautious about making absolute claims without sufficient evidence.
That's why you need to have enough data to get reliable results that will make your research project make sense statistically, logically, conceptually, theoretically, and even emotionally 😇
