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Originally Posted by roflwaffle
Someone would need more than just another brand/model. Many brands/models for many years would be needed. Even then, no where in the paper is the relationship bigger = better mentioned, you were the only one who mentioned it...........
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It is true that the presentation doesn't say larger = better, and it is also true that I have drawn that conculusion, but I am not the only person to have done so.
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Originally Posted by roflwaffle
.......In the end the author states...
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The lack of quality linear correlations between rolling resistances and the basic parameters investigated suggested that if the researcher is investigating manufacturer/tire design differences within a tire size, other more complex aspects of the tire will need to be considered.
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So what they are stating is entirely reasonable given the data, and there were no objections because of that. You were the one who stated bigger = better, and that is where the debate is....... |
True - and perhaps I've overstated this. However, I think it is painfully obvious that larger sized tires give better RRC values than smaller sized tires - and if that were wrong, I feel confident someone would have pointed this out, particularly considering that there are regulations being written and this would be a very important thing to get right.
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Originally Posted by roflwaffle
.......In terms of a regression analysis, that's not exactly kosher. One of the assumptions of a regression analysis is that......
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The sample is representative of the population for the inference prediction
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So w/o data for larger sizes you still can't reasonably state that bigger = better even for Goodyear Integritys, and certainly not for tires in general. |
But the data
IS representative. They are all the same make and model - and you don't have to have EVERY data point to draw a conclusion.
But you are right to point out that there are risks associated with extrapolating data.
Side note: The way science works is that a phenomenon is observed and reported and some conclusions are drawn from those observations - just like I did. Then the data is examined, the analysis critiqued, other studies run, etc. - all with the idea of trying to refute the conclusion. If the conclusion stands up to scrutiny, then it is accepted - until further data comes along. We are in the critique phase - and I have no problem with anyone critiquing, questioning, etc.