Conditional probability computation

In summary, the candidate C's probability of losing the election decreases by 1/0.8 after he withdraws from the race.
  • #1
Nero26
21
1
Hi all,
While solving problems related to probability I got stucked with this problem:
In some election 4 candidates A,B,C,D has the probability of being elected is 0.4,0.3,0.2,0.1 respectively.If the candidate C discard his candidateship just prior to the election ,then what will be the current probability of the remaining three?
I thought a lot but couldn't find any way to relate the probability of C with others.I sensed the probability of others will increase but I'm unable to determine it.By the way,my knowledge is limited to topics like conditional probability,Bayes' Theorem.But I can't categorize the problem in any formula.If the problem is explained please remain in the scope of my knowledge.
Or do I have to learn some new concept to solve this type of problem?
Any help will be appreciated.
Thanks.
 
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  • #2
Nero26 said:
Hi all,
While solving problems related to probability I got stucked with this problem:
In some election 4 candidates A,B,C,D has the probability of being elected is 0.4,0.3,0.2,0.1 respectively.If the candidate C discard his candidateship just prior to the election ,then what will be the current probability of the remaining three?
I thought a lot but couldn't find any way to relate the probability of C with others.I sensed the probability of others will increase but I'm unable to determine it.By the way,my knowledge is limited to topics like conditional probability,Bayes' Theorem.But I can't categorize the problem in any formula.If the problem is explained please remain in the scope of my knowledge.
Or do I have to learn some new concept to solve this type of problem?
Any help will be appreciated.
Thanks.

It is not possible to give a good, convincing answer to this question. For example, you don't know whether the supporters of C will stay home and not vote at all, or whether some of them will vote instead for A, B or D, and the proportions who do so.

I suspect that what the questioner wants you to do is look at the problem in a rather naive manner, as though the supporters of A, B, C and D were like four types of objects in a large bin (in the proportions indicated), and then get the new proportions after all the type C objects have been removed from the bin.

RGV
 
Last edited:
  • #3
Ray Vickson said:
It is not possible to give a good, convincing answer to this question. For example, you don't know whether the supporters of C will stay home and not vote at all, or whether some of them will vote instead for A, B or D, and the proportions who do so.

I suspect that what the questioner wants you to do is look at the problem in a rather naive manner, as though the supporters of A, B, C and D were like four types of objects in a large bin (in the proportions indicated), and then get the new proportions after all the type C objects have been removed from the bin.

RGV
Oh!you're really great.:smile:Thanks a lot.I solved it according to your instructions.Considering there were 100 voters.So when C left,20 voters left or didn't participate in election.So now among 80 voters A,B,D have 40,30,10 supporters respectively.This way their probability gets changed to 40/80,30/80,10/80 which matches the answers.
By the way,actually it is a problem in our book and I referred to its solution manual of my friend :devil:.They solved this simple problem in such a strange way that both the problem and its solution seemed very difficult to understand.Here it is:
"Solution: probability of defeat of C was =1-.2=0.8
As C left,the probability of win of each of the remaining will increase by 1/0.8=1.25 times.(Can you please say how they did it?)
So probabilities of win of A,B,D are 0.4*1.25,0.3*1.25,0.1*1.25 or 0.5,0.375,0.125 respectively."
Because of you people we can :biggrin:
 

FAQ: Conditional probability computation

1. What is conditional probability computation?

Conditional probability computation is a method used to calculate the probability of an event occurring given that another event has already occurred. It takes into account the relationship between the two events, known as the conditional probability, and is often used in real-world scenarios to make predictions.

2. How is conditional probability computed?

Conditional probability is computed by dividing the probability of the joint occurrence of the two events by the probability of the first event occurring. This can be represented mathematically as P(A|B) = P(A∩B) / P(B), where P(A|B) is the conditional probability of event A given event B has occurred, P(A∩B) is the joint probability of both events occurring, and P(B) is the probability of event B occurring.

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

Unconditional probability refers to the probability of an event occurring without any prior knowledge or conditions. On the other hand, conditional probability takes into account the relationship between two events and uses that information to calculate the probability of one event occurring given that the other event has already occurred.

4. How is conditional probability useful in real life?

Conditional probability is useful in real life for making predictions and decisions based on past events. For example, it can be used in the medical field to determine the likelihood of a patient having a certain disease based on their symptoms and medical history. It is also used in finance to assess the risk of investing in certain stocks based on market conditions.

5. Are there any limitations to conditional probability computation?

One limitation of conditional probability computation is that it assumes independence between the two events. In reality, events may be dependent on each other and this can affect the accuracy of the calculation. Additionally, it requires accurate and unbiased data to be effective, so any errors or biases in the data can also affect the results.

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