It may not be an official bias, but the “but there’s still a chance, right” outlook looks a lot like the sharply rising curve of the subjective probability function near zero.
(RETRACTED) This is an official bias, known as the certainty effect. (/RETRACTED)
EDIT (thanks, Vaniver): This is closely related to the certainty effect, which describes the sharp change in weighting near p=1 when an outcome switches from a sure thing to merely a likely possibility. The sharp change in weighting near p=0 is similar, as an outcome switches from an impossibility to merely an unlikely possibility, but I don’t think it has a handy name.
That looks like something else, actually- that’s the sharply falling weight near 1, as uncertain things aren’t as valuable as certain things. Yvain is discussing when people model a tiny chance of winning as much larger- as vividly displayed by the lottery, for example.
You’re right; comment retracted/edited. I’d thought that it referred to the sharp changes in weight near 1 and 0, but a little bit of googling confirms that the term is only applied to the change near 1.
(RETRACTED) This is an official bias, known as the certainty effect. (/RETRACTED)
EDIT (thanks, Vaniver): This is closely related to the certainty effect, which describes the sharp change in weighting near p=1 when an outcome switches from a sure thing to merely a likely possibility. The sharp change in weighting near p=0 is similar, as an outcome switches from an impossibility to merely an unlikely possibility, but I don’t think it has a handy name.
That looks like something else, actually- that’s the sharply falling weight near 1, as uncertain things aren’t as valuable as certain things. Yvain is discussing when people model a tiny chance of winning as much larger- as vividly displayed by the lottery, for example.
You’re right; comment retracted/edited. I’d thought that it referred to the sharp changes in weight near 1 and 0, but a little bit of googling confirms that the term is only applied to the change near 1.
.