Conditional probability question

In summary, an insurance company has three offices, A, B, and C, with 30% of employees in A, 20% in B, and 50% in C. In office A, 10% are managers, in office B 20% are managers, and in office C 5% are managers. The total proportion of managers in the company is 9.5%. The probability of a randomly chosen manager working in office A is 31.58%.
  • #1
fobster
3
0
An insurance company runs three offices, A, B and C. The company's employess are distirbuted as follows; 30% work in office A, 20% in Off. B and 50% in Off. C.
In office A 10% are managers, in office B 20% are managers and in office C 5% are managers

a. What is the total proportion of managers in the company?
b. If a member of staff, randomly chosen, turns out to be a manager, what is the probability that she works in office A.

I've worked out part a, (0.3*0.1)+(0.2*0.2)+(0.5*0.05)=0.03+0.04+0.025=0.0 95 or 9.5%

I'm uncertian about part b though, I think it has something to do with conditional probability which is p(b given a)=p(a and b) divided by p(a), I think.

Thanks for the help. Edit: I did probability after calculus, but I don't know about the rest of you. That's why I posted it here.
 
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  • #2
Well, you know the chance of a person being a manager; you also know the chance of the person being BOTH a manager and in office A, so you've got what you need to find out the chance of a manager being in A..
 
  • #3
So is this right?

p(a manager and in office A)=0.3*0.1=0.03

p(a manager)=0.095

0.03/0.095=0.31579
 
  • #4
Should be right.
 

1. What is conditional probability?

Conditional probability is the likelihood of an event occurring given that another event has already occurred. It takes into account prior knowledge or information about the situation.

2. How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of the two events occurring together by the probability of the condition being met. This can be represented as P(A|B) = P(A and B)/P(B).

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

Regular probability considers the likelihood of an event occurring without any prior knowledge or conditions. Conditional probability takes into account a specific condition or event that has already occurred.

4. Can you give an example of conditional probability in real life?

One example of conditional probability in real life is the probability of getting a red card in a deck of cards. If we already know that the first card drawn was a heart, the probability of drawing a red card as the second card would be higher compared to drawing any card without any prior knowledge.

5. How is conditional probability used in scientific research?

Conditional probability is commonly used in scientific research to analyze and interpret data. It can help researchers understand the relationship between different variables and how one variable may affect the likelihood of another occurring. This can also help in making predictions and developing models to understand complex systems.

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