What is the Conditional Probability of Selecting Box B Given a White Ball?

In summary, the probability of selecting a white ball using Bayes Rule is 1/6 and the conditional probability of B being selected given that the ball is white is 1/3.
  • #1
naspek
181
0
box A contains 2 red balls,
box B contains 2 white balls,
box C contains 1 red ball and 1 white ball,

A box is selected at random (with equal probabilities) and one ball is taken at random from that box.

(i) Compute the probability of selecting a white ball using Bayes Rule.

A(1/3) _____ Red(1/6)
...|____ Red(1/6)

B(1/3)______White(1/6)
...|_____White(1/6)

C(1/3)______Red(1/6)
...|_____White(1/6)

so.. P(White) = [(1/3)*(1/6)] + [(1/3)*(1/6)] + [(1/3)*(1/6)]
= 1/6

Correct?


(ii)Compute the conditional probability that B has been selected given that the ball is white.

P(B|White) = P(B intersect White) / P(White)

what is my P(B intersect White)?
 
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  • #2
P(B intersect White) = P(B) * P(White|B) = (1/3) * (1/6) = 1/18Therefore, P(B|White) = P(B intersect White)/P(White) = (1/18)/(1/6) = 1/3
 

Related to What is the Conditional Probability of Selecting Box B Given a White Ball?

1. What is conditional probability?

Conditional probability is a measure of the likelihood of an event occurring given that another event has already occurred. It is denoted as P(A|B), where A is the event of interest and B is the event that has already occurred.

2. How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of the joint events (P(A and B)) by the probability of the condition (P(B)). In other words, P(A|B) = P(A and B) / P(B).

3. What is the difference between conditional probability and joint probability?

Conditional probability is the probability of an event occurring given that another event has already occurred, while joint probability is the probability of two events occurring simultaneously. Conditional probability takes into account a known condition, while joint probability considers all possible outcomes.

4. How is conditional probability used in real life?

Conditional probability is used to understand the relationship between two events and to make predictions based on known information. It can be applied in various fields such as finance, medicine, and marketing to analyze data and make informed decisions.

5. What is the significance of Bayes' theorem in conditional probability?

Bayes' theorem is a mathematical formula that describes the relationship between conditional probabilities. It allows us to update our beliefs about an event based on new evidence, making it a fundamental tool in understanding conditional probability and making predictions.

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