Why New Cars Lose Much Value When Driven Off Lot

“The day that a car is driven off the lot is the worst day in its life, for it instantly loses as much as a quarter of its value. This might seem absurd, but we know it to be true. A new car that was bought for $20,000 cannot be resold for more than perhaps $15,000. Why? Because the only person who might logically want to resell a brand-new car is someone who found the car to be a lemon. So even if the car isn’t a lemon, a potential buyer assumes that it is. He assumes that the seller has some information about the car that he, the buyer, does not have–and the sell is punished for this assumed information.”(p. 67)

Direct Instruction Teaching Method Invalidly Challenged By Michigan Study

“…Critics try to discredit [Direct Instruction] by arguing that DI causes antisocial behavior. At public meetings, whenever the possibility of switching to DI is mentioned, someone is sure to bring up a Michigan study claiming that students who are taught with DI are more likely to be arrested in their adolescent years. Here’s evidence, they say, that DI is dangerous. The problem is that this randomized study was based on the experience of just sixty-eight students. And the students in the DI and the control groups were not similar. In the end, the Michigan study is just window dressing. The education establishment is wedded to its pet theories regardless of what the evidence says.” (p. 164-165)

Data Mining Techniques May Threaten Traditional Jobs

“The rise of Super Crunching threatens the status and respectability of many traditional jobs…Following some other guy’s script or algorithm may not make for the most interesting job, but time and time again it leads to a more effective business model. We are living in an age where dispersed discretion is on the wane. This is not the end of discretion; it’s the shift of discretion from line employees to the much more centralized staff os Super Crunching higher-ups…Marx was wrong about a lot of things, but through a Super Crunching lens, eh looks downright prescient when he said that the development of capitalism would increasingly alienate workers from their work-product.” (p. 166-167)

Getting People to Accept Statistical / Data Mining Approaches

“There’s almost an iron-clad law that it’s easier for people to warm up to applications of Super Crunching outside of their own area of expertise. It’s devilishly hard for traditional, non-empirical evaluators to even consider the possibility that quantified predictions might do a better job than they can on their own home turf. I don’t think this is primarily because of blatant self-interest in trying to keep our jobs. We humans just overestimate our ability to make good decisions and we’re skeptical that a formula that necessarily ignores innumerable pieces of information could do a better job than we could.” (p. 150)

Humans Are Bad At Making Predictions

“The human mind tends to suffer from a number of well-documented cognitive failings and biases that distort our ability to predict accurately. We tend to give too much weight to unusual events that seem salient…Once we form a mistaken belief about something, we tend to cling to it. As new evidence arrives, we’re likely to discount disconfirming evidence and focus instead on evidence that supports our preexisting beliefs.” (p. 112)