Exclusion-inclusion formula in probability

In summary, the conversation discusses proving the inclusion-exclusion formula for a probability space by induction. The attempt at a solution involves breaking down the problem into simpler cases and using the properties of unions and intersections to show that the formula holds for n=2. The final step is to show that the formula holds for n to (n+1) by defining a new set of events and using the properties of unions and intersections again. It is suggested to first try the cases of going from n=2 to n=3 and from n=3 to n=4 to better understand the process before attempting the general case.
  • #1
mahler1
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Homework Statement



Let ##(\Omega,\mathcal F, P)## be a probability space and let ##A_1,A_2,...,A_n## be events in ##\mathcal F##.

Prove the following inclusion-exclusion formula

##P(\bigcup_{i=1}^nA_i)=\sum_{k=1}^n## ##\sum_{\mathcal J \subset \{1,...,n\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)##


The Attempt at a Solution



I am trying to prove this formula by induction; for ##n=2##, let ##A, B## be two events in ##\mathcal F##. We can write ##A=(A \setminus B) \cup (A\cap B)##, ##B=(B \setminus A) \cup (A\cap B)##, since these are disjoint unions, then

##P(A)=P(A \setminus B)+P(A\cap B)## and ##P(B)=P(B \setminus A)+P(A\cap B)##.

Now, ##A \cup B## can be expressed as ##A \cup B= (A\setminus B) \cup (A \cap B) \cup (B \setminus A)##, which it's also union of disjoint sets, so

##P(A \cup B)=P(A \setminus B)+P(A\cap B)+P(B \setminus A)=P(A)+P(B)-P(A \cap B)##.

This proves that for ##n=2##, the formula is correct.

Now, I want to show that the formula is true for ##n \implies## the formula is satisfied for ##n+1##

I define ##B_1=A_1,\ldots,B_{n-1}=A_{n-1},B_n=A_n\cup A_{n+1}##. We have

##P(\cup_{i=1}^n B_i)=\sum_{\mathcal J \subset \{1,...,n\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} B_i)##.

This equals to ##\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)+\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k-1} (-1)^{k}P(\bigcap_{i \in \mathcal J} A_i \cap (A_n \cup A_{n+1}))##

##=\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)+\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k-1} (-1)^k(P(\bigcap_{i \in \mathcal J} A_i \cap A_n)+ P(\bigcap_{i \in \mathcal J} A_i \cap A_{n+1})-P(\bigcap_{i \in \mathcal J} A_i \cap A_n \cap A_{n+1}))##.

I don't know how to reduce this expression to the one I need to, which is:

##\sum_{\mathcal J \subset \{1,...,n+1\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)##


I would really appreciate some help to finish the problem.
 
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  • #2
mahler1 said:

Homework Statement



Let ##(\Omega,\mathcal F, P)## be a probability space and let ##A_1,A_2,...,A_n## be events in ##\mathcal F##.

Prove the following inclusion-exclusion formula

##P(\bigcup_{i=1}^nA_i)=\sum_{k=1}^n## ##\sum_{\mathcal J \subset \{1,...,n\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)##


The Attempt at a Solution



I am trying to prove this formula by induction; for ##n=2##, let ##A, B## be two events in ##\mathcal F##. We can write ##A=(A \setminus B) \cup (A\cap B)##, ##B=(B \setminus A) \cup (A\cap B)##, since these are disjoint unions, then

##P(A)=P(A \setminus B)+P(A\cap B)## and ##P(B)=P(B \setminus A)+P(A\cap B)##.

Now, ##A \cup B## can be expressed as ##A \cup B= (A\setminus B) \cup (A \cap B) \cup (B \setminus A)##, which it's also union of disjoint sets, so

##P(A \cup B)=P(A \setminus B)+P(A\cap B)+P(B \setminus A)=P(A)+P(B)-P(A \cap B)##.

This proves that for ##n=2##, the formula is correct.

Now, I want to show that the formula is true for ##n \implies## the formula is satisfied for ##n+1##

I define ##B_1=A_1,\ldots,B_{n-1}=A_{n-1},B_n=A_n\cup A_{n+1}##. We have

##P(\cup_{i=1}^n B_i)=\sum_{\mathcal J \subset \{1,...,n\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} B_i)##.

This equals to ##\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)+\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k-1} (-1)^{k}P(\bigcap_{i \in \mathcal J} A_i \cap (A_n \cup A_{n+1}))##

##=\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)+\sum_{\mathcal J \subset \{1,...,n-1\}; |\mathcal J|=k-1} (-1)^k(P(\bigcap_{i \in \mathcal J} A_i \cap A_n)+ P(\bigcap_{i \in \mathcal J} A_i \cap A_{n+1})-P(\bigcap_{i \in \mathcal J} A_i \cap A_n \cap A_{n+1}))##.

I don't know how to reduce this expression to the one I need to, which is:

##\sum_{\mathcal J \subset \{1,...,n+1\}; |\mathcal J|=k} (-1)^{k+1}P(\bigcap_{i \in \mathcal J} A_i)##


I would really appreciate some help to finish the problem.

Instead of trying to jump immediately to the general case, first try the simple cases of going from n=2 to n=3 and from n=3 to n=4 (and no, I am not joking). That way, you will see what is happening, and be able to grasp how to go the the general case of n to (n+1).
 
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FAQ: Exclusion-inclusion formula in probability

1. What is the exclusion-inclusion formula in probability?

The exclusion-inclusion formula in probability is a method used to calculate the probability of the union of two or more events. It takes into account the overlap between the events to avoid double counting.

2. How is the exclusion-inclusion formula applied?

The exclusion-inclusion formula is applied by taking the sum of the individual probabilities of the events, subtracting the probabilities of their intersections, adding back the probabilities of their intersections of three events, and so on until all possible combinations have been accounted for.

3. Why is the exclusion-inclusion formula useful?

The exclusion-inclusion formula is useful because it allows for the calculation of the probability of complex events that cannot be directly calculated using traditional methods. It also helps to avoid overcounting and provides a more accurate estimation of probabilities.

4. What are the limitations of the exclusion-inclusion formula?

One limitation of the exclusion-inclusion formula is that it becomes increasingly complex and time-consuming when applied to events with more than three or four components. It also assumes that the events are independent of each other, which may not always be the case.

5. Can the exclusion-inclusion formula be applied to non-mutually exclusive events?

Yes, the exclusion-inclusion formula can be applied to non-mutually exclusive events. In this case, the formula would still work, but the probabilities of the intersections would need to be adjusted accordingly to account for the overlap between the events.

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