I'm sorry Count Iblis, here's my reply:
Umm, Count Iblis, you are wrong. It's the other way around. A p value less than 0.05 represents a deviation from the null hypothesis. And it's got nothing to do with a hypothetical reality.
eg a p value of 0.03 proves a significant difference, there is only a 3% chance that the difference is due to chance, and a 97% chance that there is a significant difference. A p value of 0.7 suggests a 70% chance that any deviation is due to chance, and a 30% prob that it isn't. Other way around mate.
"This sort of simplisic tests are not the way to detect small subtle effects when you have limited data."
They are the only way
"You can always assume some null model and then say that you didn't detect a significant deviation from the null model."
Nope wrong there. We are testing if the difference in temperature we may/may not be seeing now is due to natural variation or not. Significance tests is the only way to test this.
"You can always assume some null model and then say that you didn't detect a significant deviation from the null model."
Umm, this is completly the false way to do scientific tests. The null is always that there is no differnce, the alternate is that there is.
I am afraid you are wrong on all counts here Count Iblis, please feel free to read a 1st year statistics book.
