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Mathematics · Ch 4 — Combinatorics and Mathematical Induction

Permutations of distinct objects

4.4.1

Permutations of distinct objects

Viewed as a function, a permutation of a finite set S={x1,x2,…,xn}S=\{x_1,x_2,\ldots,x_n\} is a bijective mapping of SS onto itself; the number of permutations of SS therefore equals the total number of bijections from SS to SS, which is n!n!.

Theorem 4.1. If n,rn,r are positive integers with r≤nr\le n, the number of permutations of nn distinct objects taken rr at a time is

nPr=n(n−1)(n−2)⋯(n−r+1).^nP_r = n(n-1)(n-2)\cdots(n-r+1).

Proof idea. A permutation of rr objects out of nn fills rr positions in a row using nn distinct objects: the first position has nn choices, the second has n−1n-1 remaining choices, the third has n−2n-2, ..., and the rrth position has n−(r−1)n-(r-1) choices left. By the rule of product, nPr=n(n−1)(n−2)⋯(n−r+1)^nP_r=n(n-1)(n-2)\cdots(n-r+1).

Theorem 4.2. For n≥1n\ge1, 0≤r≤n0\le r\le n,

nPr=n!(n−r)!.^nP_r = \frac{n!}{(n-r)!}.

Proof. Multiply and divide Theorem 4.1's product by (n−r)!(n-r)!:

nPr=n(n−1)⋯(n−r+1)=n(n−1)⋯(n−r+1)×(n−r)(n−r−1)⋯2⋅1(n−r)(n−r−1)⋯2⋅1=n!(n−r)!.^nP_r = n(n-1)\cdots(n-r+1) = \frac{n(n-1)\cdots(n-r+1)\times(n-r)(n-r-1)\cdots2\cdot1}{(n-r)(n-r-1)\cdots2\cdot1} = \frac{n!}{(n-r)!}.

Boundary values. For a positive integer nn and non-negative integer rr:

nPr={n!(n−r)!r≤n,0r>n,nPn=n!,nP0=1.^nP_r = \begin{cases} \dfrac{n!}{(n-r)!} & r\le n,\\ 0 & r>n,\end{cases} \qquad {}^nP_n=n!,\qquad {}^nP_0=1.

So arranging all nn distinct objects in a row is nPn=n!^nP_n=n! ways, matching the earlier direct count. …