Yet the first bringer of unwelcome news
Hath but a losing office, and his tongue
Sounds ever after as a sullen bell,
Remember’d tolling a departing friend.
—Henry IV, part II
So there was Nate Silver, statistician par excellence, wearing the oak leaf cluster and crown of laurel, holding a purple slide rule, riding his chariot triumphantly through the blogosphere commemorating his famous victory over Uncertainty. He had predicted a high probability Barack Obama would be re-elected to the presidency.1
The Media loved him for his divination and showered him with much praise, honors, and gold.
But riding on the chariot with Silver was one of Uncertainty’s vanquished generals who whispered into Silver’s ear, “All glory is fleeting.”
Boy, was he right. And in spades.
Because Silver has again ventured forth into battle, facing his old enemy, but this time his augury is unwanted: “GOP Is Slight Favorite in Race for Senate Control.”
The same Media who once loved him is now hot on Silver’s tail, fangs bared, pitchforks and torches waving, for the crime of foreseeing unfavorable events. Business Insider says Democrats Are Freaking Out About Nate Silver’s Latest Prediction. The National Journal leads “Democrats to Nate Silver: You’re Wrong“.
Guy Cecil, executive director of the Democratic Senatorial Campaign Committee, is not happy and insists Silver is wrong. This judgment is itself a prediction, for there is no way for Cecil to know Silver is wrong, but it’s a happy one because it tells Democrat supporters what they wish to hear. But then, even if the GOP does not re-take the Senate, it doesn’t make sense to say that Silver was wrong.
Cecil said, “In fact, in August of 2012 Silver forecast a 61 percent likelihood that Republicans would pick up enough seats to claim the majority,” but the Democrats held. Again Cecil said Silver was wrong.
But Silver wasn’t (and can’t be) wrong because there isn’t any way a (non-extreme) probability forecast can be wrong.
All probability forecasts sound like this: “Given my evidence, the probability of Q is P”. As long as P is less than 1 and greater than 0, there is uncertainty whether Q, the proposition of interest, is true. For Silver, Q = “The GOP retakes the Senate.” His evidence is proprietary and his P isn’t explicitly stated (but note that it can be calculated from the table he gives here; 20 bonus points for the reader who does it).
To be wrong, Silver’s forecast has to say P = 1 and the Democrats must retain control. There is no other way to err. If Silver’s P = 0.99 (and it isn’t), and the Dems keep regulating our lives, then Silver would still not be wrong.
There is a sense, though, that Silver’s prediction, in the light of the cold reality of the Dems holding power, might be seen as less than useful (we are imagining a future in which the GOP loses). This sense highlights the very real difference between a prediction and a decision. We’ve seen what a prediction is. A decision takes a prediction and acts on it. Decisions can be wrong. Non-extreme probability predictions cannot be.
One decision might be to bet that the GOP takes it. If the Democrats win, you lose your bet, and you lose because your decision is wrong. The prediction remains a probability, a true statement of the evidence used to create it.
Not everybody will use Silver’s prediction to bet. Why? Because some people don’t like to bet, or others like to but don’t see much pay off, or because a prediction which is just the other side of a coin flip doesn’t instill enough courage to gamble. But others might love to have a go and will plunk down lots, whether in terms of real money or in reputation points (a pundit might say “The GOP is gonna take it all!”).
Thus a prediction which is useful for one person can be of no use to another. Decisions made on predictions are so varied that there’s no way to know who, if anybody, they might be useful for. (Though there are ways to look at collections of predictions and surmise what might happen if these predictions are used for future decisions of a known sort.)
It’s clear, though, that Cecil doesn’t feel Silver’s latest clairvoyance is useful for him. If people act on Silver’s prediction such that they cease donating to Democrat candidates, thinking these candidates will lose, those candidates deprived of money will be more likely to lose. So Cecil must do what he can do to plant doubts about Silver’s prediction—and about Silver himself—even though Silver is scarcely making a bold guess.
Luckily for Cecil, the Media is ready to shoot the messenger for him.
1Many statisticians of lesser repute, such as Yours Truly, have done much worse.