So the correct answer is 0.1698 approximately. And to compute this, I used the trick I’ve shown you before. Let me write down the running count for cancer, and for not cancer, as I integrate the various multiplications in Bayes rule. My prior for cancer was 0.01, and for non-cancer was 0.99. Then I get my first +, and the probability of a plus given that we have cancer is 0.9. And the same for non cancer is 0.2. So according to the non-normalized Bayes rule, I now multiply these two things together to get my non-normalized probability of having cancer given the plus. Since multiplication is commutative, I can do the same thing again with my second test result, 0.9, 0.2. And I multiply all of these three things together to get my non normalized probability, P prime, to be the following. 0.0081 if you multiply those things together. And 0.0396 if you multiply these guys together. And these are not a probability. If we add those for the two complementary, with cancer, non cancer, I get 0.0477. However, I now divide. That is, I normalize those non normalized probabilities over here by this factor over here. I actually get the correct posterior probability. P(C) given ++. And they look as follows, approximately 0.1698 and approximately 0.8301.