Mathematics Exam  >  Mathematics Notes  >  Mathematics for IIT JAM, GATE, CSIR NET, UGC NET  >  Inclusion Exclusion Principle - Algebra, CSIR-NET Mathematical Sciences

Inclusion Exclusion Principle - Algebra, CSIR-NET Mathematical Sciences | Mathematics for IIT JAM, GATE, CSIR NET, UGC NET PDF Download

Download, print and study this document offline
Please wait while the PDF view is loading
 Page 1


Lecture 9
The Principle of
Inclusion/Exclusion
These notes are based on a pair of lectures originally written by (Manchester’s own)
Prof. Nige Ray.
Reading:
The Principle of Inclusion/Exclusion appears in the ?rst year module Foundations
of Pure Mathematics, but it is also a standard technique in Combinatorics and so
is discussed in many other books
1
. The Wikipedia article, which gives a version of
the proof in Section 9.2.2 below, is also a good place to start.
9.1 Introduction: a familiar example
Supposewehavesome?nite“universal”setU andtwosubsets,X
1
? U andX
2
? U.
If the subsets are disjoint then it’s easy to work out the number of elements in their
union:
X
1
\ X
2
=;) |X
1
[ X
2
| = |X
1
|+ |X
2
|.
The case where the subsets have a non-empty intersection provides the simplest in-
stanceoftheresultwe’regoingtodeveloptoday,thePrincipleofInclusion/Exclusion.
You may already know a similar result from Probability.
Lemma 9.1 (Inclusion/Exclusion for two sets). If X
1
and X
2
are ?nite sets then
|X
1
[ X
2
| = |X
1
|+ |X
2
| |X
1
\ X
2
|. (9.1)
Note that this formula, which is illustrated in Figure 9.1, works even X
1
\ X
2
=; ,
as then |X
1
\ X
2
|=0.
Proof. To prove this result, note that the sum |X
1
|+ |X
2
| counts each member of
the intersectionX
1
\ X
2
twice, once as a member ofX
1
and then again as a member
1
See, for example, Dossey, Otto, Spence, and Vanden Eynden (2006), Discrete Mathematics or,
for a short, clear account, Anderson (1974), A First Course in Combinatorial Mathematics.
Page 2


Lecture 9
The Principle of
Inclusion/Exclusion
These notes are based on a pair of lectures originally written by (Manchester’s own)
Prof. Nige Ray.
Reading:
The Principle of Inclusion/Exclusion appears in the ?rst year module Foundations
of Pure Mathematics, but it is also a standard technique in Combinatorics and so
is discussed in many other books
1
. The Wikipedia article, which gives a version of
the proof in Section 9.2.2 below, is also a good place to start.
9.1 Introduction: a familiar example
Supposewehavesome?nite“universal”setU andtwosubsets,X
1
? U andX
2
? U.
If the subsets are disjoint then it’s easy to work out the number of elements in their
union:
X
1
\ X
2
=;) |X
1
[ X
2
| = |X
1
|+ |X
2
|.
The case where the subsets have a non-empty intersection provides the simplest in-
stanceoftheresultwe’regoingtodeveloptoday,thePrincipleofInclusion/Exclusion.
You may already know a similar result from Probability.
Lemma 9.1 (Inclusion/Exclusion for two sets). If X
1
and X
2
are ?nite sets then
|X
1
[ X
2
| = |X
1
|+ |X
2
| |X
1
\ X
2
|. (9.1)
Note that this formula, which is illustrated in Figure 9.1, works even X
1
\ X
2
=; ,
as then |X
1
\ X
2
|=0.
Proof. To prove this result, note that the sum |X
1
|+ |X
2
| counts each member of
the intersectionX
1
\ X
2
twice, once as a member ofX
1
and then again as a member
1
See, for example, Dossey, Otto, Spence, and Vanden Eynden (2006), Discrete Mathematics or,
for a short, clear account, Anderson (1974), A First Course in Combinatorial Mathematics.
U
X
1
X
2
U
X
1
X
1
n X
2
X
2
Figure 9.1: In the example at left X
1
\ X
2
=; , so |X
1
[ X
2
| = |X
1
|+|X
2
|, but in the
example at right X
1
\ X
2
6=; and so |X
1
[ X
2
| = |X
1
|+|X
2
| |X
1
\ X
2
| < |X
1
|+|X
2
|.
U
X
1
\ X
2
X
1
n X
2
X
2
\ X
1
Figure 9.2: Here X
1
\X
2
and X
1
\ X
2
are shown in shades of blue, while X
2
\X
1
is
in yellow.
of X
2
. Subtracting |X
1
\ X
2
| corrects for this double-counting. Alternatively, for
those who prefer proofs that look more like calculations, begin by de?ning
X
1
\X
2
= {x2 U | x2 X
1
, butx/ 2 X
2
}.
Then, as is illustrated in Figure 9.2, X
1
=(X
1
\X
2
)[ (X
1
\ X
2
). Further, the sets
X
1
\X
2
and X
1
\ X
2
are disjoint by construction, so
|X
1
| = |X
1
\X
2
|+ |X
1
\ X
2
| or |X
1
\X
2
| = |X
1
| |X
1
\ X
2
|. (9.2)
Similarly, X
1
\X
2
and X
2
are disjoint and X
1
[ X
2
=(X
1
\X
2
)[ X
2
so
|X
1
[ X
2
| = |X
1
\X
2
|+ |X
2
|
= |X
1
| |X
1
\ X
2
|+ |X
2
|
= |X
1
|+ |X
2
| |X
1
\ X
2
|
where, in passing from the ?rst line to the second, we have used (9.2). The last line
is the result we were trying to prove, so we are ?nished.
9.2 Principle and proof
Before moving to the general case, let’s consider one more small example, this
time with three subsets X
1
, X
2
and X
3
: we can handle this case by clever use
Page 3


Lecture 9
The Principle of
Inclusion/Exclusion
These notes are based on a pair of lectures originally written by (Manchester’s own)
Prof. Nige Ray.
Reading:
The Principle of Inclusion/Exclusion appears in the ?rst year module Foundations
of Pure Mathematics, but it is also a standard technique in Combinatorics and so
is discussed in many other books
1
. The Wikipedia article, which gives a version of
the proof in Section 9.2.2 below, is also a good place to start.
9.1 Introduction: a familiar example
Supposewehavesome?nite“universal”setU andtwosubsets,X
1
? U andX
2
? U.
If the subsets are disjoint then it’s easy to work out the number of elements in their
union:
X
1
\ X
2
=;) |X
1
[ X
2
| = |X
1
|+ |X
2
|.
The case where the subsets have a non-empty intersection provides the simplest in-
stanceoftheresultwe’regoingtodeveloptoday,thePrincipleofInclusion/Exclusion.
You may already know a similar result from Probability.
Lemma 9.1 (Inclusion/Exclusion for two sets). If X
1
and X
2
are ?nite sets then
|X
1
[ X
2
| = |X
1
|+ |X
2
| |X
1
\ X
2
|. (9.1)
Note that this formula, which is illustrated in Figure 9.1, works even X
1
\ X
2
=; ,
as then |X
1
\ X
2
|=0.
Proof. To prove this result, note that the sum |X
1
|+ |X
2
| counts each member of
the intersectionX
1
\ X
2
twice, once as a member ofX
1
and then again as a member
1
See, for example, Dossey, Otto, Spence, and Vanden Eynden (2006), Discrete Mathematics or,
for a short, clear account, Anderson (1974), A First Course in Combinatorial Mathematics.
U
X
1
X
2
U
X
1
X
1
n X
2
X
2
Figure 9.1: In the example at left X
1
\ X
2
=; , so |X
1
[ X
2
| = |X
1
|+|X
2
|, but in the
example at right X
1
\ X
2
6=; and so |X
1
[ X
2
| = |X
1
|+|X
2
| |X
1
\ X
2
| < |X
1
|+|X
2
|.
U
X
1
\ X
2
X
1
n X
2
X
2
\ X
1
Figure 9.2: Here X
1
\X
2
and X
1
\ X
2
are shown in shades of blue, while X
2
\X
1
is
in yellow.
of X
2
. Subtracting |X
1
\ X
2
| corrects for this double-counting. Alternatively, for
those who prefer proofs that look more like calculations, begin by de?ning
X
1
\X
2
= {x2 U | x2 X
1
, butx/ 2 X
2
}.
Then, as is illustrated in Figure 9.2, X
1
=(X
1
\X
2
)[ (X
1
\ X
2
). Further, the sets
X
1
\X
2
and X
1
\ X
2
are disjoint by construction, so
|X
1
| = |X
1
\X
2
|+ |X
1
\ X
2
| or |X
1
\X
2
| = |X
1
| |X
1
\ X
2
|. (9.2)
Similarly, X
1
\X
2
and X
2
are disjoint and X
1
[ X
2
=(X
1
\X
2
)[ X
2
so
|X
1
[ X
2
| = |X
1
\X
2
|+ |X
2
|
= |X
1
| |X
1
\ X
2
|+ |X
2
|
= |X
1
|+ |X
2
| |X
1
\ X
2
|
where, in passing from the ?rst line to the second, we have used (9.2). The last line
is the result we were trying to prove, so we are ?nished.
9.2 Principle and proof
Before moving to the general case, let’s consider one more small example, this
time with three subsets X
1
, X
2
and X
3
: we can handle this case by clever use
U
X
1
X
2
X
1
X
2
X
3
Figure 9.3: In the diagram above all of the intersections appearing in Eqn. (9.3) are
nonempty.
of Lemma 9.1 from the previous section. If we regard (X
1
[ X
2
)asasinglesetand
X
3
as a second set, then Eqn. (9.1) says
|(X
1
[ X
2
)[ X
3
| = |(X
1
[ X
2
)|+ |X
3
| |(X
1
[ X
2
)\ X
3
|
=(|X
1
|+ |X
2
| |X
1
\ X
2
|)+ |X
3
| |(X
1
[ X
2
)\ X
3
|
= |X
1
|+ |X
2
|+ |X
3
| |X
1
\ X
2
| |(X
1
[ X
2
)\ X
3
|
Focusing on the ?nal term, we can use standard relations about unions and inter-
sections to say
(X
1
[ X
2
)\ X
3
=(X
1
\ X
3
)[ (X
2
\ X
3
).
Then, applying Eqn. (9.1) to the pair of sets (X
1
\ X
3
)and(X
2
\ X
3
), we obtain
|(X
1
[ X
2
)\ X
3
| = |(X
1
\ X
3
)[ (X
2
\ X
3
)|
= |X
1
\ X
3
|+ |X
2
\ X
3
| |(X
1
\ X
3
)\ (X
2
\ X
3
)|
= |X
1
\ X
3
|+ |X
2
\ X
3
| |X
1
\ X
2
\ X
3
|
where, in going from the second line to the third, we have used
(X
1
\ X
3
)\ (X
2
\ X
3
)= X
1
\ X
2
\ X
3
.
Finally, putting all these results together, we obtain the analogue of Eqn. (9.1)
for three subsets:
|(X
1
[ X
2
)[ X
3
| = |X
1
|+ |X
2
|+ |X
3
| |X
1
\ X
2
| |(X
1
[ X
2
)\ X
3
|
= |X
1
|+ |X
2
|+ |X
3
| |X
2
\ X
3
|
 (|X
1
\ X
3
|+ |X
2
\ X
3
| |(X
1
\ X
2
\ X
3
|)
=(|X
1
|+ |X
2
|+ |X
3
|)
 (|X
1
\ X
2
|+ |X
1
\ X
3
|+ |X
2
\ X
3
|)
+ |X
1
\ X
2
\ X
3
|. (9.3)
Figure 9.3 helps make sense of this formula and prompts the following observations:
Page 4


Lecture 9
The Principle of
Inclusion/Exclusion
These notes are based on a pair of lectures originally written by (Manchester’s own)
Prof. Nige Ray.
Reading:
The Principle of Inclusion/Exclusion appears in the ?rst year module Foundations
of Pure Mathematics, but it is also a standard technique in Combinatorics and so
is discussed in many other books
1
. The Wikipedia article, which gives a version of
the proof in Section 9.2.2 below, is also a good place to start.
9.1 Introduction: a familiar example
Supposewehavesome?nite“universal”setU andtwosubsets,X
1
? U andX
2
? U.
If the subsets are disjoint then it’s easy to work out the number of elements in their
union:
X
1
\ X
2
=;) |X
1
[ X
2
| = |X
1
|+ |X
2
|.
The case where the subsets have a non-empty intersection provides the simplest in-
stanceoftheresultwe’regoingtodeveloptoday,thePrincipleofInclusion/Exclusion.
You may already know a similar result from Probability.
Lemma 9.1 (Inclusion/Exclusion for two sets). If X
1
and X
2
are ?nite sets then
|X
1
[ X
2
| = |X
1
|+ |X
2
| |X
1
\ X
2
|. (9.1)
Note that this formula, which is illustrated in Figure 9.1, works even X
1
\ X
2
=; ,
as then |X
1
\ X
2
|=0.
Proof. To prove this result, note that the sum |X
1
|+ |X
2
| counts each member of
the intersectionX
1
\ X
2
twice, once as a member ofX
1
and then again as a member
1
See, for example, Dossey, Otto, Spence, and Vanden Eynden (2006), Discrete Mathematics or,
for a short, clear account, Anderson (1974), A First Course in Combinatorial Mathematics.
U
X
1
X
2
U
X
1
X
1
n X
2
X
2
Figure 9.1: In the example at left X
1
\ X
2
=; , so |X
1
[ X
2
| = |X
1
|+|X
2
|, but in the
example at right X
1
\ X
2
6=; and so |X
1
[ X
2
| = |X
1
|+|X
2
| |X
1
\ X
2
| < |X
1
|+|X
2
|.
U
X
1
\ X
2
X
1
n X
2
X
2
\ X
1
Figure 9.2: Here X
1
\X
2
and X
1
\ X
2
are shown in shades of blue, while X
2
\X
1
is
in yellow.
of X
2
. Subtracting |X
1
\ X
2
| corrects for this double-counting. Alternatively, for
those who prefer proofs that look more like calculations, begin by de?ning
X
1
\X
2
= {x2 U | x2 X
1
, butx/ 2 X
2
}.
Then, as is illustrated in Figure 9.2, X
1
=(X
1
\X
2
)[ (X
1
\ X
2
). Further, the sets
X
1
\X
2
and X
1
\ X
2
are disjoint by construction, so
|X
1
| = |X
1
\X
2
|+ |X
1
\ X
2
| or |X
1
\X
2
| = |X
1
| |X
1
\ X
2
|. (9.2)
Similarly, X
1
\X
2
and X
2
are disjoint and X
1
[ X
2
=(X
1
\X
2
)[ X
2
so
|X
1
[ X
2
| = |X
1
\X
2
|+ |X
2
|
= |X
1
| |X
1
\ X
2
|+ |X
2
|
= |X
1
|+ |X
2
| |X
1
\ X
2
|
where, in passing from the ?rst line to the second, we have used (9.2). The last line
is the result we were trying to prove, so we are ?nished.
9.2 Principle and proof
Before moving to the general case, let’s consider one more small example, this
time with three subsets X
1
, X
2
and X
3
: we can handle this case by clever use
U
X
1
X
2
X
1
X
2
X
3
Figure 9.3: In the diagram above all of the intersections appearing in Eqn. (9.3) are
nonempty.
of Lemma 9.1 from the previous section. If we regard (X
1
[ X
2
)asasinglesetand
X
3
as a second set, then Eqn. (9.1) says
|(X
1
[ X
2
)[ X
3
| = |(X
1
[ X
2
)|+ |X
3
| |(X
1
[ X
2
)\ X
3
|
=(|X
1
|+ |X
2
| |X
1
\ X
2
|)+ |X
3
| |(X
1
[ X
2
)\ X
3
|
= |X
1
|+ |X
2
|+ |X
3
| |X
1
\ X
2
| |(X
1
[ X
2
)\ X
3
|
Focusing on the ?nal term, we can use standard relations about unions and inter-
sections to say
(X
1
[ X
2
)\ X
3
=(X
1
\ X
3
)[ (X
2
\ X
3
).
Then, applying Eqn. (9.1) to the pair of sets (X
1
\ X
3
)and(X
2
\ X
3
), we obtain
|(X
1
[ X
2
)\ X
3
| = |(X
1
\ X
3
)[ (X
2
\ X
3
)|
= |X
1
\ X
3
|+ |X
2
\ X
3
| |(X
1
\ X
3
)\ (X
2
\ X
3
)|
= |X
1
\ X
3
|+ |X
2
\ X
3
| |X
1
\ X
2
\ X
3
|
where, in going from the second line to the third, we have used
(X
1
\ X
3
)\ (X
2
\ X
3
)= X
1
\ X
2
\ X
3
.
Finally, putting all these results together, we obtain the analogue of Eqn. (9.1)
for three subsets:
|(X
1
[ X
2
)[ X
3
| = |X
1
|+ |X
2
|+ |X
3
| |X
1
\ X
2
| |(X
1
[ X
2
)\ X
3
|
= |X
1
|+ |X
2
|+ |X
3
| |X
2
\ X
3
|
 (|X
1
\ X
3
|+ |X
2
\ X
3
| |(X
1
\ X
2
\ X
3
|)
=(|X
1
|+ |X
2
|+ |X
3
|)
 (|X
1
\ X
2
|+ |X
1
\ X
3
|+ |X
2
\ X
3
|)
+ |X
1
\ X
2
\ X
3
|. (9.3)
Figure 9.3 helps make sense of this formula and prompts the following observations:
• Elements of X
1
[ X
2
[ X
3
that belong to exactly one of the X
j
are counted
exactly once by the sum (|X
1
|+ |X
2
|+ |X
3
|) and do not contribute to any of
the terms involving intersections.
• Elements of X
1
[ X
2
[ X
3
that belong to exactly two of the X
j
are double-
countedbythesum, (|X
1
|+ |X
2
|+ |X
3
|), butthisdouble-countingiscorrected
by the term involving two-fold intersections.
• Finally, elements of X
1
[ X
2
[ X
3
that belong to all three of the sets are
triple-counted by the initial sum (|X
1
|+ |X
2
|+ |X
3
|). This triple-counting is
then completely cancelled by the term involving two-fold intersections. Then,
?nally, this cancellation is repaired by the ?nal term, which counts each such
element once.
9.2.1 The general case
The Principle of Inclusion/Exclusion generalises the results in Eqns. (9.1) and (9.3)
to unions of arbitrarily many subsets.
Theorem 9.2 (The Principle of Inclusion/Exclusion). If U is a ?nite set and
{X
j
}
n
j=1
is a collection of n subsets, then





n
[
j=1
X
j





= |X
1
[ ···[ X
n
|
= |X
1
|+···+ |X
n
|
 |X
1
\ X
2
| ··· |X
n 1
\ X
n
|
+|X
1
\ X
2
\ X
3
|+···+ |X
n 2
\ X
n 1
\ X
n
|
.
.
.
+( 1)
m 1
X
1? i
1
? ···? im? n
|X
i
1
\ ···\ X
im
|
.
.
.
+( 1)
n 1
|X
1
\ ···\ X
n
| (9.4)
or, more concisely,
|X
1
[ ···[ X
n
| =
X
I? {1,...,n},I6=; ( 1)
|I| 1





\
i2 I
X
i





(9.5)
One can prove this in at least two ways:
• by induction, with a calculation that is essentially the same as the one used
to obtain then=3case—Eqn.(9.3)—fromthe n=2one—Eqn.(9.1);
• by showing that eachx2 X
1
[ ···[ X
n
contributes exactly one to the sum on
the right hand side of Eqn. (9.5).
The ?rst approach is straightforward, if a bit tedious, and so is left as an exercise,
but the second is more interesting and so it’s the one we’ll study here.
Page 5


Lecture 9
The Principle of
Inclusion/Exclusion
These notes are based on a pair of lectures originally written by (Manchester’s own)
Prof. Nige Ray.
Reading:
The Principle of Inclusion/Exclusion appears in the ?rst year module Foundations
of Pure Mathematics, but it is also a standard technique in Combinatorics and so
is discussed in many other books
1
. The Wikipedia article, which gives a version of
the proof in Section 9.2.2 below, is also a good place to start.
9.1 Introduction: a familiar example
Supposewehavesome?nite“universal”setU andtwosubsets,X
1
? U andX
2
? U.
If the subsets are disjoint then it’s easy to work out the number of elements in their
union:
X
1
\ X
2
=;) |X
1
[ X
2
| = |X
1
|+ |X
2
|.
The case where the subsets have a non-empty intersection provides the simplest in-
stanceoftheresultwe’regoingtodeveloptoday,thePrincipleofInclusion/Exclusion.
You may already know a similar result from Probability.
Lemma 9.1 (Inclusion/Exclusion for two sets). If X
1
and X
2
are ?nite sets then
|X
1
[ X
2
| = |X
1
|+ |X
2
| |X
1
\ X
2
|. (9.1)
Note that this formula, which is illustrated in Figure 9.1, works even X
1
\ X
2
=; ,
as then |X
1
\ X
2
|=0.
Proof. To prove this result, note that the sum |X
1
|+ |X
2
| counts each member of
the intersectionX
1
\ X
2
twice, once as a member ofX
1
and then again as a member
1
See, for example, Dossey, Otto, Spence, and Vanden Eynden (2006), Discrete Mathematics or,
for a short, clear account, Anderson (1974), A First Course in Combinatorial Mathematics.
U
X
1
X
2
U
X
1
X
1
n X
2
X
2
Figure 9.1: In the example at left X
1
\ X
2
=; , so |X
1
[ X
2
| = |X
1
|+|X
2
|, but in the
example at right X
1
\ X
2
6=; and so |X
1
[ X
2
| = |X
1
|+|X
2
| |X
1
\ X
2
| < |X
1
|+|X
2
|.
U
X
1
\ X
2
X
1
n X
2
X
2
\ X
1
Figure 9.2: Here X
1
\X
2
and X
1
\ X
2
are shown in shades of blue, while X
2
\X
1
is
in yellow.
of X
2
. Subtracting |X
1
\ X
2
| corrects for this double-counting. Alternatively, for
those who prefer proofs that look more like calculations, begin by de?ning
X
1
\X
2
= {x2 U | x2 X
1
, butx/ 2 X
2
}.
Then, as is illustrated in Figure 9.2, X
1
=(X
1
\X
2
)[ (X
1
\ X
2
). Further, the sets
X
1
\X
2
and X
1
\ X
2
are disjoint by construction, so
|X
1
| = |X
1
\X
2
|+ |X
1
\ X
2
| or |X
1
\X
2
| = |X
1
| |X
1
\ X
2
|. (9.2)
Similarly, X
1
\X
2
and X
2
are disjoint and X
1
[ X
2
=(X
1
\X
2
)[ X
2
so
|X
1
[ X
2
| = |X
1
\X
2
|+ |X
2
|
= |X
1
| |X
1
\ X
2
|+ |X
2
|
= |X
1
|+ |X
2
| |X
1
\ X
2
|
where, in passing from the ?rst line to the second, we have used (9.2). The last line
is the result we were trying to prove, so we are ?nished.
9.2 Principle and proof
Before moving to the general case, let’s consider one more small example, this
time with three subsets X
1
, X
2
and X
3
: we can handle this case by clever use
U
X
1
X
2
X
1
X
2
X
3
Figure 9.3: In the diagram above all of the intersections appearing in Eqn. (9.3) are
nonempty.
of Lemma 9.1 from the previous section. If we regard (X
1
[ X
2
)asasinglesetand
X
3
as a second set, then Eqn. (9.1) says
|(X
1
[ X
2
)[ X
3
| = |(X
1
[ X
2
)|+ |X
3
| |(X
1
[ X
2
)\ X
3
|
=(|X
1
|+ |X
2
| |X
1
\ X
2
|)+ |X
3
| |(X
1
[ X
2
)\ X
3
|
= |X
1
|+ |X
2
|+ |X
3
| |X
1
\ X
2
| |(X
1
[ X
2
)\ X
3
|
Focusing on the ?nal term, we can use standard relations about unions and inter-
sections to say
(X
1
[ X
2
)\ X
3
=(X
1
\ X
3
)[ (X
2
\ X
3
).
Then, applying Eqn. (9.1) to the pair of sets (X
1
\ X
3
)and(X
2
\ X
3
), we obtain
|(X
1
[ X
2
)\ X
3
| = |(X
1
\ X
3
)[ (X
2
\ X
3
)|
= |X
1
\ X
3
|+ |X
2
\ X
3
| |(X
1
\ X
3
)\ (X
2
\ X
3
)|
= |X
1
\ X
3
|+ |X
2
\ X
3
| |X
1
\ X
2
\ X
3
|
where, in going from the second line to the third, we have used
(X
1
\ X
3
)\ (X
2
\ X
3
)= X
1
\ X
2
\ X
3
.
Finally, putting all these results together, we obtain the analogue of Eqn. (9.1)
for three subsets:
|(X
1
[ X
2
)[ X
3
| = |X
1
|+ |X
2
|+ |X
3
| |X
1
\ X
2
| |(X
1
[ X
2
)\ X
3
|
= |X
1
|+ |X
2
|+ |X
3
| |X
2
\ X
3
|
 (|X
1
\ X
3
|+ |X
2
\ X
3
| |(X
1
\ X
2
\ X
3
|)
=(|X
1
|+ |X
2
|+ |X
3
|)
 (|X
1
\ X
2
|+ |X
1
\ X
3
|+ |X
2
\ X
3
|)
+ |X
1
\ X
2
\ X
3
|. (9.3)
Figure 9.3 helps make sense of this formula and prompts the following observations:
• Elements of X
1
[ X
2
[ X
3
that belong to exactly one of the X
j
are counted
exactly once by the sum (|X
1
|+ |X
2
|+ |X
3
|) and do not contribute to any of
the terms involving intersections.
• Elements of X
1
[ X
2
[ X
3
that belong to exactly two of the X
j
are double-
countedbythesum, (|X
1
|+ |X
2
|+ |X
3
|), butthisdouble-countingiscorrected
by the term involving two-fold intersections.
• Finally, elements of X
1
[ X
2
[ X
3
that belong to all three of the sets are
triple-counted by the initial sum (|X
1
|+ |X
2
|+ |X
3
|). This triple-counting is
then completely cancelled by the term involving two-fold intersections. Then,
?nally, this cancellation is repaired by the ?nal term, which counts each such
element once.
9.2.1 The general case
The Principle of Inclusion/Exclusion generalises the results in Eqns. (9.1) and (9.3)
to unions of arbitrarily many subsets.
Theorem 9.2 (The Principle of Inclusion/Exclusion). If U is a ?nite set and
{X
j
}
n
j=1
is a collection of n subsets, then





n
[
j=1
X
j





= |X
1
[ ···[ X
n
|
= |X
1
|+···+ |X
n
|
 |X
1
\ X
2
| ··· |X
n 1
\ X
n
|
+|X
1
\ X
2
\ X
3
|+···+ |X
n 2
\ X
n 1
\ X
n
|
.
.
.
+( 1)
m 1
X
1? i
1
? ···? im? n
|X
i
1
\ ···\ X
im
|
.
.
.
+( 1)
n 1
|X
1
\ ···\ X
n
| (9.4)
or, more concisely,
|X
1
[ ···[ X
n
| =
X
I? {1,...,n},I6=; ( 1)
|I| 1





\
i2 I
X
i





(9.5)
One can prove this in at least two ways:
• by induction, with a calculation that is essentially the same as the one used
to obtain then=3case—Eqn.(9.3)—fromthe n=2one—Eqn.(9.1);
• by showing that eachx2 X
1
[ ···[ X
n
contributes exactly one to the sum on
the right hand side of Eqn. (9.5).
The ?rst approach is straightforward, if a bit tedious, and so is left as an exercise,
but the second is more interesting and so it’s the one we’ll study here.
9.2.2 Proof
The key idea is to think of the the elements of X
1
[ ···[ X
n
individually and
ask what each one contributes to the sum in Eqn. (9.5). Suppose that an element
x 2 X
1
[ ···[ X
n
belongs to exactly ` of the subsets, with 1 ? ` ? n: we will
prove that x makes a net contribution of 1. For the sake of concreteness, we’ll say
x2 X
i
1
,...,X
i
`
where i
1
,...,i
`
are distinct elements of {1,...,n}.
• As we’ve assumed that x belongs to exactly ` of the subsets X
j
, it contributes
atotalof ` to the ?rst row, |X
1
|+···+ |X
n
|, of the long sum in Eqn. (9.4).
• Further, x contributes a total of 
`
2

to the sum in the row involving two-way
intersections
 |X
1
\ X
2
| ··· |X
n 1
\ X
n
|.
To see this, note that if x2 X
j
\ X
k
then both j and k must be members of
the set {i
1
,...,i
`
}.
• Similar arguments show that if k? `, then x contributes a total of
( 1)
k 1
?
`
k
?
=( 1)
k 1
?
`!
k!(` k)!
?
to the sum in the row of Eqn. (9.4) that involves k-fold intersections.
• Finally, fork> ` there are no k-fold intersections that contain x and so x
makes a contribution of zero to the corresponding rows in Eqn. (9.4).
Putting these observations together we see that x make a net contribution of
` ?
`
2
?
+
?
`
3
?
 ... +( 1)
` 1
?
`
`
?
(9.6)
This sum can be made to look more familiar by considering the following application
of the Binomial Theorem:
0= (1 1)
`
=
`
X
j=0
( 1)
j
(1)
` j
?
`
j
?
=1 `+
?
`
2
?
 ?
`
3
?
+ ... +( 1)
`
?
`
`
?
.
Thus
0= 1 ?
` ?
`
2
?
+
?
`
3
?
 ... +( 1)
` 1
?
`
`
?
or
` ?
`
2
?
+
?
`
3
?
 ... +( 1)
` 1
?
`
`
?
=1.
The left hand side here is the same as the sum in Eqn. (9.6) and so we’ve established
that any x which belongs to exactly ` of the subsets X
j
makes a net contribution of 1
to the sum on the right hand side of Eqn. (9.5). And as every x2 X
1
[ ···[ X
n
must
belongtoatleastoneoftheX
j
, thisestablishesthePrincipleofInclusion/Exclusion.
Read More
556 videos|198 docs

FAQs on Inclusion Exclusion Principle - Algebra, CSIR-NET Mathematical Sciences - Mathematics for IIT JAM, GATE, CSIR NET, UGC NET

1. What is the Inclusion-Exclusion Principle in algebra?
Ans. The Inclusion-Exclusion Principle is a principle used in algebra to calculate the total number of elements in the union or intersection of multiple sets. It provides a systematic approach to account for overlapping elements and avoid double counting.
2. How does the Inclusion-Exclusion Principle work?
Ans. The Inclusion-Exclusion Principle involves adding the sizes of individual sets, subtracting the sizes of pairwise intersections, adding the sizes of triple intersections, and so on. This alternating addition and subtraction process helps to account for overlapping elements and obtain the correct count.
3. What is the significance of the Inclusion-Exclusion Principle in combinatorics?
Ans. The Inclusion-Exclusion Principle is highly significant in combinatorics as it allows us to calculate the cardinality of complicated sets or events. It provides a powerful tool to solve counting problems involving multiple sets and helps in deriving formulas for counting arrangements, permutations, or combinations.
4. Can the Inclusion-Exclusion Principle be applied to any number of sets?
Ans. Yes, the Inclusion-Exclusion Principle can be applied to any number of sets. Whether it is two sets, three sets, or even more, the principle remains the same. It involves adding and subtracting the sizes of various intersections to obtain the correct count.
5. Is the Inclusion-Exclusion Principle useful in solving algorithmic problems?
Ans. Yes, the Inclusion-Exclusion Principle is useful in solving algorithmic problems, especially in the field of computer science. It provides an efficient approach to count or calculate probabilities in situations where multiple events or conditions are involved. By applying the principle, programmers can optimize their algorithms and solve complex counting or probability-related challenges.
556 videos|198 docs
Download as PDF
Explore Courses for Mathematics exam
Signup for Free!
Signup to see your scores go up within 7 days! Learn & Practice with 1000+ FREE Notes, Videos & Tests.
10M+ students study on EduRev
Related Searches

CSIR-NET Mathematical Sciences | Mathematics for IIT JAM

,

MCQs

,

shortcuts and tricks

,

GATE

,

Sample Paper

,

Important questions

,

Previous Year Questions with Solutions

,

Inclusion Exclusion Principle - Algebra

,

practice quizzes

,

GATE

,

Free

,

pdf

,

ppt

,

UGC NET

,

Inclusion Exclusion Principle - Algebra

,

Objective type Questions

,

Summary

,

CSIR-NET Mathematical Sciences | Mathematics for IIT JAM

,

Extra Questions

,

UGC NET

,

GATE

,

CSIR-NET Mathematical Sciences | Mathematics for IIT JAM

,

Inclusion Exclusion Principle - Algebra

,

Exam

,

video lectures

,

past year papers

,

study material

,

Viva Questions

,

CSIR NET

,

mock tests for examination

,

UGC NET

,

CSIR NET

,

Semester Notes

,

CSIR NET

;