What a debate about p-values shows about science
I personally find NHST suspicious, even if the p-value is less than 0.005. It means that, ASSUMING that the null hypothesis is correct, the probability of observing the data is less than 0.5%. That&#x27;s still not zero, though. For example, if I try to decide that native Hawaiians are US citizens, and the null hypothesis is that they are, but since only ~0.2% of total US population is native Hawaiian, NHST would conclude that native Hawaiians aren&#x27;t US citizens. Conversely, the p-value being high isn&#x27;t really meaningful either. For example, if I try to decide if a white person is from South Africa, and the null hypothesis is that they are, and since ~9% of the population in South Africa is white, I would fail to reject the null hypothesis, even if the person&#x27;s actually from Europe or literally any other country in the world. p-values are dependent on the sample size, too, and become more and more sensitive to smaller differences in the ASSUMED population distribution(s), when the effect size can in fact be small. NSHT seems highly dependent on quality null hypothesis that&#x27;s correct, which you can&#x27;t really establish since that&#x27;s what you&#x27;re trying to find out. So the approach doesn&#x27;t really conclude anything either way, and just really seems weak as an approach to scientific testing overall.