By William Feller

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45 . Calculate P(A|B) . 4. The buildings in a district can roughly be characterized as either housing area or industrial zone. We study here emergency calls due to alarm. 55. 05. The ﬁre brigade returns to the station after a mission, they have put out a ﬁre. Calculate the probability that they have returned from a mission to an industrial zone. 5. When coded messages are sent, errors in transmission sometimes occur. Consider Morse code, where “dots” and “dashes” are used. It is known that the odds for dot sent versus dash sent is 3:4.

Top: Arithmetic mean x ¯= x − p)/p . · · · + xn ) . Bottom: Relative error (¯ 1 (x1 n + x2 + ✬ ✩ Long-term frequencies. Deﬁne a sequence of independent random variables Xi as follows ⎧ ⎨ 1, if the statement A about the outcome of the ith experiment is true, Xi = ⎩ 0, otherwise. ¯= Again, by LLN, X ✫ 1 n (X1 + X2 + · · · + Xn ) → p , where p = P(A). ✪ Here we interpret the probability P(A) as observed long-term frequencies when the statement A about a result of an experiment is true. In most computations of risks, one wishes to give probabilities interpretations as frequencies of times when A is true.

In the literature, it is suggested that the intensity of ﬁres starting in these types of buildings is equal to the ﬂoor area times a factor α , say, taking values between 10−6 and 4 · 10−6 ([year −1 m −2 ]). 5 · 106 m 2 . (a) As values of α , the consultant chooses 10−6 , 2 · 10−6 , 3 · 10−6 , and 4 · 10−6 . Based on this choice, help her to estimate intensities and formulate suitable prior odds for Λ . (b) Suppose during the ﬁrst two months, no ﬁres were reported. Use this information to update the prior odds.