Conditional probability equation, how is it derived?

In summary, conditional probability is the chance of an event A happening, given that another event B has occurred. The formula for calculating conditional probability is P(A|B) = P(AnB)/P(B). This concept is useful in situations where the knowledge of one event affects the probability of another event occurring. It is also important to note that conditional probability is based on different sets of information and can only be applied to events that are dependent on each other.
  • #1
Werg22
1,431
1
I have to admit I'm struck odd by the this definition:

P(A|B) = P(AnB)/P(B)

I know conditional probability is the "chance of event a dependant even B happening, given A happens". But really, I don't quite get it... what is meant?
 
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  • #2
Werg22 said:
I have to admit I'm struck odd by the this definition:

P(A|B) = P(AnB)/P(B)

I know conditional probability is the "chance of event a dependant even B happening, given A happens". But really, I don't quite get it... what is meant?

A simple example: imagine you're throwing a single dice. What is the probability that you'll get an even number under the condition that the number is less than 4?
 
  • #3
Well the probability of getting an even number is 3/6 and the probability of getting a number under 4 is 3/6 as well. The final answer is 1/6... but I don't see how this connects to the formula.
 
  • #4
Werg22 said:
Well the probability of getting an even number is 3/6 and the probability of getting a number under 4 is 3/6 as well. The final answer is 1/6... but I don't see how this connects to the formula.

The answer is not 1/6.Think about the question "what is the probability that you roll an even number under the condition that the number rolled is less than 4"

The given condition is that the number rolled is less than 4, ie it is 1,2 or 3. Now, you want the probability that the number rolled is even. Since there is only on even number in the set {1,2,3} then the answer to the given question is 1/3.

This has everything to do with the formula above. Use your values in the equation:

P(even|<4)= P(even and <4)/P(<4) = (1/6)/(3/6)=1/3

edit: sorry to jump in radou.. i didnt see you were still online!
 
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  • #5
Werg22 said:
I have to admit I'm struck odd by the this definition:

P(A|B) = P(AnB)/P(B)

I know conditional probability is the "chance of event a dependant even B happening, given A happens". But really, I don't quite get it... what is meant?

The crucial point about "conditional probability" is that you move from calculations of probabilities within one set of known information to do calculations within ANOTHER set of known information, and that moving from one knowledge set to another may influence the computed probability.

For example, the probabilities P(B) and P(A and B) are calculated with respect to a set of known information that does NOT include any knowledge of whether A or B has happened.

The probability P(A|B), however, is simply the probability of A happening WITHIN THE INFORMATION SET WHERE THE KNOWLEDGE OF B HAVING HAPPENED is included! (Thus, for example, P(B|B) must necessarily equal 1, and P(not B|B) is necessarily 0)

The relation P(A and B)=P(A|B)*P(B) therefore relates probabilities calculated with respect to different sets of knowledge.

Events of such a nature that the knowledge of either one of them does not influence the probability of the other one occurring, relative to the information set where neither outcome is known, are called INDEPENDENT events.
 
  • #6
Ok thanks allot guys! I'm pretty sure I understand now. So the definition of P(A|B) "probability of an element of set A happening in set B". Say, A has 4 elements that are common to set B and set B has 8 elements, then the probability is 4/8. Right?
 
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  • #7
That is correct.
 

1. What is conditional probability?

Conditional probability is a mathematical concept that measures the likelihood of an event occurring given that another event has already occurred. It is represented by the notation P(A|B), where A is the event of interest and B is the condition that has already occurred.

2. How is the conditional probability equation derived?

The conditional probability equation is derived from the basic definition of probability, which is the number of favorable outcomes divided by the total number of possible outcomes. In the case of conditional probability, the total number of possible outcomes is reduced by the condition that has already occurred.

3. Can you provide an example of how the equation is used?

Sure, let's say we want to find the probability of getting a head when flipping a coin twice. The equation would be P(H|T) = P(H and T)/P(T) = (1/4)/(1/2) = 1/2. This means that the probability of getting a head on the second flip given that the first flip was a tail is 1/2.

4. What are some real-life applications of conditional probability?

Conditional probability is widely used in various fields such as finance, engineering, and medicine. It can be used to predict stock market trends, analyze the reliability of a product, and assess the risk of developing a disease based on certain factors.

5. Are there any limitations to the use of conditional probability equation?

Yes, there are some limitations to the use of conditional probability equation. It assumes that the events are independent, meaning that the occurrence of one event does not affect the probability of another event. This may not always be the case in real-life situations, so the results may not always be accurate.

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