Question about conditional probability

In summary, the conversation discusses conditional probability and how events can either attract or repel each other based on their probabilities. It is shown that if event B attracts event A, then A also attracts B and B repels ~A. It is also discussed how ratios can be used to explain the concept of conditional probability and how it applies to specific examples involving sets and probability measures. It is proven that A and B, as well as B and C, attract each other, while A and C do not attract each other.
  • #1
Alexsandro
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0
Question about conditional probability. Can someone help me ?

Repulsion. The event A is said to be repelled by the event B is P(A|B) < P(A), and to be attracted by B P(A|B) > P(A).

(a) Show that if B attracts A, then A attracts B, and ~B repels A.

(b) If A attracts B, and B attarcts C, does A attract C?

(c) Explain this, throught ratio idea:

P(A|B) > P(A) => P(B|A) > P(B).
 
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  • #2
Use definition of cond. prob., P(A|B) = P(A & B)/P(B).

(a) B Attracts A ---> P(A & B)/P(B) > P(A) ---> P(A & B) > P(A)P(B) ---> P(A & B)/P(A) > P(B) ---> A attr. B.

B Attracts A ---> P(A & B)/P(B) > P(A) ---> (P(A)-P(A & ~B))/(1-P(~B)) > P(A) ---> P(A)-P(A & ~B) > P(A) - P(A)P(~B) ---> -P(A & ~B) > - P(A)P(~B) ---> P(A & ~B) < P(A)P(~B) ---> P(A & ~B)/P(~B) < P(A) ---> ~B repels A.

(c) See (a).
 
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  • #3
(b) Counterex.

Let S = {1,2,2,3,4,5}
A = {x is in S : x is even} = {2,2,4}
B = {x is in S : x < 3} = {1,2,2}
C = {x is in S : x is boldface} = {1,2,5}

"P" is the uniform prob. measure over the elements of S.

A and B attract each other.
Proof: P(A & B) = P({2,2}) = 1/3 > 1/4 = P(A)P(B).

B and C attract each other.
Proof: P(B & C) = P({1,2}) = 1/3 > 1/4 = P(B)P(C).

A and C do not attract each other.
Proof: P(A & C) = P({2}) = 1/6 < 1/4 = P(A)P(C) ---> A and C repel.
 
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1. What is conditional probability?

Conditional probability is the likelihood of an event occurring, given that another event has already occurred. It is the probability of event A happening, given that event B has occurred.

2. How is conditional probability calculated?

Conditional probability is calculated by dividing the probability of both events occurring by the probability of the first event occurring. This can be written as P(A|B) = P(A and B) / P(B).

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

The main difference is that regular probability considers the likelihood of an event occurring without taking into account any other events. Conditional probability, on the other hand, takes into account the occurrence of another event.

4. Can conditional probability be greater than 1?

Yes, conditional probability can be greater than 1. This occurs when the probability of the second event occurring given the first event has happened is greater than the probability of the first event occurring.

5. How is conditional probability used in real life?

Conditional probability is used in various real-life scenarios, such as weather forecasting, medical diagnoses, and risk assessment. It helps in making predictions and decisions based on the likelihood of an event occurring, given the occurrence of another event.

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