I love positive articles about Tesla and Model S's, but articles talking about the statisticians at iSeeCars.com and this amazing outcome they're seeing leads me to 1 of 2 conclusions:
1) the statisticians DO have a clue and are being badly misquoted by their own firm, and then further badly misquoted by the press writing these articles
2) the statisticians are clueless, and I wouldn't want them close to anything resembling a business decision my company needs to make.
What do I get from the numbers quoted by Forbes and others?
1) People buying Model S's option up their cars a lot. Much more than Tesla expected early on, though it now appears the option dense choices we make are built into their planning.
2) Comparing the used sale price of highly optioned cars to the new purchase price of base models is not the basis for drawing a meaningful conclusion
3) Forbes observation that the price was that high despite the fact that a used buyer wouldn't get the benefit of the $7500 tax credit is indeed a meaningful and useful contribution to the dialogue.
It could easily be the case that in the detailed data, there is evidence supporting precisely the conclusion being drawn. I relatively straightforward method of collection would be to generate what each of those used cars would cost to purchase new today as a comparison price, and then figure out how much the car has depreciated when it's sold. Maybe also stir in how long the car was owned or how many miles driven. And then that depreciation rate can be compared to other cars in the market range to draw a conclusion about how the Model S is holding up relative to competition.
I don't like short articles that twist a subset of available facts to draw a conclusion critical of the company or the stock, and I don't like articles that twist a subset of available facts to draw a conclusion that supports the company. Both are misleading and dishonest.
It would be nice to see the raw data the statisticians were working with though....
