It’s much more natural way how to think about it (cf eg TE Janes, Probability theory, examples in Chapter IV)
In this specific case of evaluating hypothesis, the distance in the logodds space indicates the strength the evidence you would need to see to update. Close distance implies you don’t that much evidence to update between the positions (note the distance between 0.7 and 0.2 is closer than 0.9 and 0.99). If you need only a small amount of evidence to update, it is easy to imagine some other observer as reasonable as you had accumulated a bit or two somewhere you haven’t seen.
Because working in logspace is way more natural, it is almost certainly also what our brains do—the “common sense” is almost certainly based on logspace representations.
It’s much more natural way how to think about it (cf eg TE Janes, Probability theory, examples in Chapter IV)
In this specific case of evaluating hypothesis, the distance in the logodds space indicates the strength the evidence you would need to see to update. Close distance implies you don’t that much evidence to update between the positions (note the distance between 0.7 and 0.2 is closer than 0.9 and 0.99). If you need only a small amount of evidence to update, it is easy to imagine some other observer as reasonable as you had accumulated a bit or two somewhere you haven’t seen.
Because working in logspace is way more natural, it is almost certainly also what our brains do—the “common sense” is almost certainly based on logspace representations.