CP-Clarification

CP-Clarification - Conditional Probability Clarification of...

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Conditional Probability Clarification of Tree View Ramesh Yerraballi
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Tree View In the tree view for conditional probability each node represents an event of interest to us. The branches of the tree are labeled by the probabilities that the branch in question is taken, i.e., the occurrence probability leading from one to the next node. Here is the example we looked in class: P(F) P(F c ) P(S | F) P(S c | F) P(S c | F c ) P(S | F c ) F F c S F S c F S c F c S F c F: Event that the first doctor made a positive diagnosis P(F) = 0.1 (10%) S: Event that the second doctor made a positive diagnosis P(S) = 0.17 (17%) F S : Event that both doctors made a positive diagnosis P(F S) = 0.08 (8%) We are asked to find, “the probability that the second doctor makes a positive diagnosis given that the first has made a negative diagnosis”: P(S | F c ) By definition of Conditional probability: P(S | F c ) = P(S F c ) / P(F c ) = (P(S) - P(F S)) / (1-P(F c ) = (0.17 - 0.08) / (1 - 0.9) = 0.1
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This note was uploaded on 02/01/2011 for the course BME 335 taught by Professor Dunn during the Spring '10 term at University of Texas.

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CP-Clarification - Conditional Probability Clarification of...

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