Peter Szolovits wrote:
If TWC is really calibrated, then your conditions 5 and 6 are false, no?
I agree with Peter's solution. If I build a model for this problem, it
must contain at least two variables: Snow and TWC_report. According with
my model, the TWC forecasts are calibrated if and onl
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The "Bayes ratio" (or odds ratio) interpretation of Bayes rule is enlightening,
since it reveals the strength of evidence in a way not clear from just looking
at the probabilities.
A 5% prior chance becomes odds of 1:19 against snow.
With Paul's assigned sensitivity (probability of sno
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Thank you for your many responses. You've provided at least 5 distinct answers
which I summarize below.
(Answer 5 below is clearly correct, but leads me to a new quandary.)
Answer 1: "70% chance of snow" is just a label and conceptually should be
treated as "XYZ". In other word
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Dear Paul,
if you consider TWC prediction as a part of the probabilistic model,
you get 4 probabilities for modelling a model which needs 3
probabilities to be specified.
(the model is given by the 2-way table given by (Snow/not snow and
snow prediction of 70%/not snow prediction of 70%).