If you measure the same thing twice you will get two different answers. If you measure the same thing on different occasions you will get different answers because the thing will have aged. If you measure different individuals, they will differ for both genetic and environmental reasons (nature and nurture). Heterogeneity is universal: spatial heterogeneity means that places always differ and temporal heterogeneity means that times always differ.
Because everything varies, finding that things vary is simply not interesting. We need a way of discriminating between variation that is scientifically interesting, and variation that just reflects background heterogeneity. That is why we need statistics. It is what this whole book is about.
The key concept is the amount of variation that we would expect to ocur by chance alone, when nothing scientifically intersting was going on...
....when nothing really is going on, then we want to know this. It makes life much simpler if we can be reasonably sure that there is no relationship between y and x. Some students think that 'the only good result is a significant result'. They feel that their study has somehow failed if it shows that 'A has no significant effect on B'. This is an understandable failing of human nature, but it is not good science. The point is that we want to know the truth one way or the other.
from Statistics: An Introduction using R, by Michael J. Crawley, a book which it is already impossible not to love.
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