Re: freight car distribution - rejecting the equal distribution hypothesis.

Stokes John

Well, I got thoroughly chastised and sneered at by the resident statistical intellectuals because I questioned the state of undress, then along come some other people asking cogent questions about all this, and Mike asks logical and pertinent questions again. It still seems to me that this is all hogwash about the national statistics as they may apply to and be useful for predicting how many SP box cars will be seen on the Inside Gateway on April 23, 1956 (stayed within the magic time frame, Tim). Random doesn't mean predictable, except that you can predict that it will be random. Dictionary definition of random is "lacking aim or method; purposeless; haphazard." In statistics it means "of statistical sample selection in which all possible samples have equal probability of selection." Maybe we are applying random walk here, Tim, or random variables, where the variable's values are determined independently according to a probability distribution? Predictability means capable of being predicted, which means to say in advance what one believes will happen. Yes, you can predict that the percentages of box cars in a given freight train will be random, but you say they will be in a set percentage that does not vary. Round and round we go.

Quantum physicists know about this. A random event cannot be predicted or duplicated, it's a Surprise! Almost everything is predictable, but many outcomes are very difficult to predict because the variables that drive the outcome are either unknown or difficult to measure. That is precisely what we are dealing with here. While we can get the stats on the nationwide freight car fleet, and somehow come to the conclusion that this percentage holds true as the box cars travel around the nation, each following as if by magic its random predictable pattern and percentage, the fact is that there are a whole host of variables that drive the outcome and we either don't know them all or we don't have enough information to do anything with them.

This is like playing a video game, it exercises the mind and the keeps one's juices flowing, but in the end it is virtually meaningless and not necessarily a good way to spend one's time, especially when one realizes that there are so many models to build and run and so little time to do it in.

Bye bye,

John Stokes
Bellevue, Wa

To: STMFC@...: brockm@...: Mon, 18 Aug 2008 17:20:08 -0400Subject: Re: [STMFC] Re: freight car distribution - rejecting the equal distribution hypothesis.

We are getting to the point...not unlike discussions about color...where weare not seeing anything new. So...we are getting to the point where thethread will need to be terminated. Obviously some members are convincedregarding the Nelson/Gilbert theory's validity and others are not. Before the thread is terminated...until new data becomesavailable, I would appreciate seeing some clarification on a few points.Tony Thompson writes:"I personally think Tim's data say very clearly that theappearance of free-running cars like box cars DID follow,statistically, not absolutely with mathematical precision (Tim neversaid anything like that, so let's drop it now), the proportions in thenational car fleet."What does that mean? In the 1947 data covering Laramie to Green River, thetheory predicts [ I guess that's a good word ] 28 SP box cars. The actual number was 34...a 20% error. In the 1949 data, the theory predicts 52 SP box cars. The actual number was 136...or an error of 161%. Now...when I have mentioned this before, the answer was...nooo problem. This is statistics. OK...fine. No argument. Suppose that damned UP train with the 36 SP box cars was in Fraley's sample. Now the error would be 230%. What if 5 more such trains showed up? 576%. What if it were 1000%? Or 10000%? When does it become a problem...or are the violating SP numbers just thrown away? If the reply to this is that an error of 161% is OK, why bother with the individual national %? Just take the acceptable SP number of 136 = .01 (Y) (1325 box cars), Y = 10.2% and use it for all RR's? After all, SP's national % of 3.6% is fairly representative of all RR's except for PRR and NYC. Just add 5% more for them. I guarantee that the "error" between the actual national % for CGA, Rutland or FEC won't produce a worse error than using the actual SP national % does with the Fraley 1949 data. And, it will be a lot easier to do...don't have to look up anything. Of course, the same thing can be achieved by just acquiring the same number of cars for every RR except PRR and NYC. Get two of each of those. Then do the same thing 3 more times until you have 4 cars of every RR except PRR and NYC which you will have 8 of. I guarantee that will get you in the envelop of statistical success just as much as taking ther national % for each RR."The point is that it's theunderlying reality. Anyone who doesn't have better data than Tim's willjust have to get used to it."As far As I know, Tim's data was the 1947 Fraley and the Southern RR data on a train in Asheville. I gave Tim a copy of my Fraley [ 1949 ]. Did he use any other data of actual car reports?Mike Brock

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