In mathematics , Pascal's rule is a combinatorial identity about binomial coefficients . It states that for any natural number n we have
(
n
−
1
k
)
+
(
n
−
1
k
−
1
)
=
(
n
k
)
for
1
≤
k
≤
n
{\displaystyle {n-1 \choose k}+{n-1 \choose k-1}={n \choose k}\quad {\text{for }}1\leq k\leq n}
where
(
n
k
)
{\displaystyle {n \choose k}}
is a binomial coefficient. This is also commonly written
(
n
k
)
+
(
n
k
−
1
)
=
(
n
+
1
k
)
for
1
≤
k
≤
n
+
1
{\displaystyle {n \choose k}+{n \choose k-1}={n+1 \choose k}\quad {\text{for }}1\leq k\leq n+1}
Combinatorial proof [ edit ]
Pascal's rule has an intuitive combinatorial meaning. Recall that
(
a
b
)
{\displaystyle {a \choose b}}
counts in how many ways can we pick a subset with b elements out from a set with a elements. Therefore, the right side of the identity
(
n
k
)
{\displaystyle {n \choose k}}
is counting how many ways can we get a k -subset out from a set with n elements.
Now, suppose you distinguish a particular element 'X' from the set with n elements. Thus, every time you choose k elements to form a subset there are two possibilities: X belongs to the chosen subset or not.
If X is in the subset, you only really need to choose k − 1 more objects (since it is known that X will be in the subset) out from the remaining n − 1 objects. This can be accomplished in
(
n
−
1
k
−
1
)
{\displaystyle n-1 \choose k-1}
ways.
When X is not in the subset, you need to choose all the k elements in the subset from the n − 1 objects that are not X . This can be done in
(
n
−
1
k
)
{\displaystyle n-1 \choose k}
ways.
We conclude that the numbers of ways to get a k -subset from the n -set, which we know is
(
n
k
)
{\displaystyle {n \choose k}}
, is also the number
(
n
−
1
k
−
1
)
+
(
n
−
1
k
)
.
{\displaystyle {n-1 \choose k-1}+{n-1 \choose k}.}
See also Bijective proof .
Algebraic proof [ edit ]
We need to show
(
n
k
)
+
(
n
k
−
1
)
=
(
n
+
1
k
)
.
{\displaystyle {n \choose k}+{n \choose k-1}={n+1 \choose k}.}
(
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+
(
n
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−
1
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=
n
!
k
!
(
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!
+
n
!
(
k
−
1
)
!
(
n
−
k
+
1
)
!
=
n
!
[
n
+
1
−
k
k
!
(
n
+
1
−
k
)
!
+
k
k
!
(
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+
1
−
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)
!
]
=
n
!
(
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k
!
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+
1
−
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)
!
=
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)
{\displaystyle {\begin{aligned}{n \choose k}+{n \choose k-1}&={\frac {n!}{k!(n-k)!}}+{\frac {n!}{(k-1)!(n-k+1)!}}\\&=n!\left[{\frac {n+1-k}{k!(n+1-k)!}}+{\frac {k}{k!(n+1-k)!}}\right]\\&={\frac {n!(n+1)}{k!(n+1-k)!}}={\binom {n+1}{k}}\end{aligned}}}
Generalization [ edit ]
Let
n
,
k
1
,
k
2
,
k
3
,
…
,
k
p
,
p
∈
N
∗
{\displaystyle n,k_{1},k_{2},k_{3},\dots ,k_{p},p\in \mathbb {N} ^{*}\,\!}
and
n
=
k
1
+
k
2
+
k
3
+
⋯
+
k
p
{\displaystyle n=k_{1}+k_{2}+k_{3}+\cdots +k_{p}\,\!}
. Then
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1
−
1
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k
2
,
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3
,
…
,
k
p
)
+
(
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k
1
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−
1
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,
…
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)
+
⋯
+
(
n
−
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k
1
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,
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3
,
…
,
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p
−
1
)
=
(
n
−
1
)
!
(
k
1
−
1
)
!
k
2
!
k
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!
⋯
k
p
!
+
(
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!
k
1
!
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1
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!
k
3
!
⋯
k
p
!
+
⋯
+
(
n
−
1
)
!
k
1
!
k
2
!
k
3
!
⋯
(
k
p
−
1
)
!
=
k
1
(
n
−
1
)
!
k
1
!
k
2
!
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!
⋯
k
p
!
+
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2
(
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1
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!
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1
!
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!
⋯
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+
⋯
+
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(
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!
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1
!
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!
⋯
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!
=
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+
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+
⋯
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!
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!
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⋯
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=
n
(
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!
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!
⋯
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=
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⋯
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=
(
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)
.
{\displaystyle {\begin{aligned}&{}\quad {n-1 \choose k_{1}-1,k_{2},k_{3},\dots ,k_{p}}+{n-1 \choose k_{1},k_{2}-1,k_{3},\dots ,k_{p}}+\cdots +{n-1 \choose k_{1},k_{2},k_{3},\dots ,k_{p}-1}\\&={\frac {(n-1)!}{(k_{1}-1)!k_{2}!k_{3}!\cdots k_{p}!}}+{\frac {(n-1)!}{k_{1}!(k_{2}-1)!k_{3}!\cdots k_{p}!}}+\cdots +{\frac {(n-1)!}{k_{1}!k_{2}!k_{3}!\cdots (k_{p}-1)!}}\\&={\frac {k_{1}(n-1)!}{k_{1}!k_{2}!k_{3}!\cdots k_{p}!}}+{\frac {k_{2}(n-1)!}{k_{1}!k_{2}!k_{3}!\cdots k_{p}!}}+\cdots +{\frac {k_{p}(n-1)!}{k_{1}!k_{2}!k_{3}!\cdots k_{p}!}}={\frac {(k_{1}+k_{2}+\cdots +k_{p})(n-1)!}{k_{1}!k_{2}!k_{3}!\cdots k_{p}!}}\\&={\frac {n(n-1)!}{k_{1}!k_{2}!k_{3}!\cdots k_{p}!}}={\frac {n!}{k_{1}!k_{2}!k_{3}!\cdots k_{p}!}}={n \choose k_{1},k_{2},k_{3},\dots ,k_{p}}.\end{aligned}}}
See also [ edit ]
Sources [ edit ]
External links [ edit ]