Exercise


May 08'23

Answer

Solution: C

Let [math]X[/math] and [math]Y[/math] represent the number of selected patients with early stage and advanced stage cancer, respectively. We need to calculate [math]\operatorname{E}(Y | X ≥ 1) [/math].

From conditioning on whether or not X ≥ 1 , we have

[[math]] \operatorname{E}(Y ) =\operatorname{P}[ X =0]\operatorname{E}(Y | X =0) + \operatorname{P}[ X ≥ 1]\operatorname{E}(Y | X ≥ 1) . [[/math]]

Observe that [math]\operatorname{P}[X=0] = (1-0.2)^6 = (0.8)^6 [/math], [math]\operatorname{P}[X \geq 1] = 1- \operatorname{P}[X = 0] = 1-(0.8)^6[/math], and [math]\operatorname{E}[Y] = 6(0.1) = 0.6 [/math]. Also, note that if none of the 6 selected patients have early stage cancer, then each of the 6 selected patients would independently have conditional probability [math]\frac{0.1}{1-0.2} = \frac{1}{8}[/math] of having late stage cancer, so [math]\operatorname{E}[Y | X = 0] = 6(1/8) = 0.75 [/math].

Therefore

[[math]] \operatorname{E}(Y | X \geq 1) = \frac{\operatorname{E}(Y) − \operatorname{P}[ X= 0]\operatorname{E}(Y | X= 0)}{\operatorname{P}[X \leq 1]} = \frac{0.6 − (0.8)6 (0.75)}{1-(0.8)^6} = 0.547. [[/math]]

Copyright 2023. The Society of Actuaries, Schaumburg, Illinois. Reproduced with permission.

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