Quote:
Originally Posted by Robin_NL
Serious post:
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Or can we just dismiss this type of laptime leaderboards and which one is correct if any?
Why do carmags/journos etc do lap their cars on different tracks, just for nothing? Is Hockenheim Short/GP more important than Magny-Cours and why?
The Mother of all Tracks(Nordschleife) is pretty important(doh), but every car is also driven in different circumstances/temperatures and ambient temperatures and not on the same day...
When does a laptime count? When one or two rivals are not within, let's say 1 second of the car currently driven? That would be strange....
And who decides if/when a laptime counts/is valid vs the rest?
-Some Bimmerpost forummembers?
-The carjournos/ the guys who drove the car and made it possible?
-???
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Concluding that two cars have the same performance is not dismissing results. It maybe a boring and unfavorable result to forum readers, but it is still a result.
The general idea of measuring whether or not one car is truly faster than another, whether one marketing campaign is better than another, etc, falls under the framework of null hypothesis testing.
The concept is to determine, without chance, whether some variant outperforms another. To do so we assume a distribution of the data, state a hypothesis, we calculate the probability of seeing the observed result given that the stated hypothesis is true, and report our findings.
In more friendly terms, the times given for each car on a specific track represent the sampling distribution of that track. We can then calculate a sample average and use a hypothesis test to test the assumption that a particular time is faster than the track average or different than a specific time. When you do this for the OP you’ll find that the Pista and the Type-R represent opposing ends of the spectrum. I.e. there is enough evidence to support that the Pista is faster than the Type-R and we might expect this conclusion to be reasonably accurate across varying tracks.
Ofcourse, there are downfalls with these assumptions and some techniques hold more validity than others. With a small sample size and unclear test conditions, it easy to logically dismiss a 2 millisecond time difference as chance. Further, if we take the hypothesis that the m2c and m3 zcp are equally as fast and calculate the probability, you’ll find that value to be > .9. In other words, it is highly likely that the two cars are equally fast. To determine whether one of them is faster than the other, we would need to run more tests and interpret those results as well.
So to answer your question more directly, an accepted way of determining whether a result is significant or not falls under the framework of hypothesis testing that has been established by mathematicians and statisticians, which has been adopted in business, engineering, STEM fields etc.