Set theory and baye's theorem problem

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Homework Help Overview

The discussion revolves around a probability problem involving set theory and Bayes' theorem, specifically focusing on calculating the conditional probability P(A2 U A3 | A1) given certain probabilities related to three projects. The original poster presents initial calculations and expresses confusion regarding the correct approach to find the solution.

Discussion Character

  • Exploratory, Mathematical reasoning, Assumption checking

Approaches and Questions Raised

  • The original poster attempts to calculate P(A2 U A3 | A1) using various probability equations but encounters difficulties. Some participants suggest considering all cases involving A1 to compute the conditional probability accurately. Others propose using a specific formulation involving Bayes' theorem to express the conditional probability in terms of known values.

Discussion Status

The discussion is ongoing, with participants exploring different methods to approach the problem. Some guidance has been offered regarding the use of Bayes' theorem, but there is no explicit consensus on the correct method or solution yet.

Contextual Notes

The original poster has calculated P(A2 U A3) but is unsure about the next steps, indicating potential gaps in understanding the application of conditional probability in this context.

bdh2991
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A computer consulting firm presently has bids out on three projects. Let Ai = {awarded project i}, for i = 1, 2, 3, and suppose that P(A1) = 0.22, P(A2) = 0.25, P(A3) = 0.29, P(A1 ∩ A2) = 0.07, P(A1 ∩ A3) = 0.09, P(A2 ∩ A3) = 0.05, P(A1 ∩ A2 ∩ A3) = 0.02.

The question is to find the probability of P(A2 U A3 | A1)

I found that A2 U A3 is equal to 0.4675 but I'm confused on which equation to use to get the rest of the answer...

I originally thought you would just do P((A2 U A3) \bigcap A1) / P(A1) but I'm not getting the correct answer...any help?
 
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There are 8 cases, you can calculate the probabilities of all of them (or at least the 4 with A1 in it) and then just calculate P(A2 U A3 | A1) based on all cases with A1.
 
Try this:

P(A2 U A3|A1) = P(A2|A1) + P(A3|A1) - P(A2,A3|A1)

and you can switch around each term using Bayes theorem to get

= [ P(A1,A2) + P(A1,A3) - P(A1,A2,A3) ] / P(A1)

if I am not mistaken

edit: Oh, I just realized that is what you said you tried. Looks like it should work to me...
 
bdh2991 said:
I originally thought you would just do P((A2 U A3) \bigcap A1) / P(A1) but I'm not getting the correct answer...any help?
What answer did you get?
 

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