Another factor, related to bad data, would be price fraud. Fraudsters deliberately price a "vehicle" low (relative to mileage) in order to attract a high number of people. They know that only a small percentage will take the bait and send cash up front for a vehicle that he doesn't intend to sell, so he wants to make sure to get the highest number of people to respond to the listing. It's a classic buyer-beware scenario, so just keep that in mind as you see good deals in the "better" zone.

There's also several cars for $299, but in the description are $2990 down...

Thats cause thats how they are classified on cars.com. Can't blame the developer. He scrapped the data correctly just some smart ass marketing guy who put up the ads cheated...

Dealing with bad data sources is like product development 101. You're not supposed to "blame" the developer, but pointing it out and expecting a fix is fair.

It's a weekend project, but even weekend projects evolve with free time.

It's a deceptive listing, but in the description on cars.com you can see that these are $299 per month for 72 months

Google Refine is a great tool for finding and fixing anomalies like this in your data sets:

http://code.google.com/p/google-refine/

Maybe a price filter? Let us manually set the minimum to $1k.