Option A, strength 103, mass 106, total score 2(103) + 106 = 312
Option B, strength 105, mass 103, total score 2(105) + 103 = 313
Oops, I might have to look at that more closely. I think you are right. The shared offset cancels out.
I assume you mean using values for the weights that correspond to importance, which isn’t necessarily 1-10. For instance, if strength is 100 times more important than mass, we’d need to have weights of 100 and 1.
Using 100 and 1 for something that is 100 times more important is correct (assuming you are able to estimate the weights (100x is awful suspicious)). Idiot procedures were using rank indicies, not real-valued weights.
But using a linear approximation is often a good first step at the very least.
agree. Linearlity is a valid assumption
The error is using uncalibrated rating from 0-10, or worse, rank indicies. Linear valued rating from 0-10 has the potential to carry the information properly, but that does not mean people can produce calibrated estimates there.
Oops, I might have to look at that more closely. I think you are right. The shared offset cancels out.
Using 100 and 1 for something that is 100 times more important is correct (assuming you are able to estimate the weights (100x is awful suspicious)). Idiot procedures were using rank indicies, not real-valued weights.
agree. Linearlity is a valid assumption
The error is using uncalibrated rating from 0-10, or worse, rank indicies. Linear valued rating from 0-10 has the potential to carry the information properly, but that does not mean people can produce calibrated estimates there.