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Permutation Solver: nPr, Repeated Elements, and Circular Arrangements

How can a permutation solver be used to count (1) r-permutations without repetition, (2) distinct permutations with repeated elements, and (3) circular permutations, and what are the results for representative examples?

Subject: Statistics Chapter: Discrete Random Variables and Their Probability Distributions Topic: Factorials Combinations and Permutations Answer included
permutation solver permutations nPr factorial arrangements order matters permutations with repetition multiset permutations
Accepted answer Answer included

Meaning of “permutation solver” in statistics

A permutation solver is a counting method (or tool) that returns how many outcomes exist when order matters. The most common situations are:

  • Choosing \(r\) distinct objects from \(n\) and arranging them (no repetition): \(nP r\).
  • Arranging \(n\) objects when some are identical (repeated elements): multiset permutations.
  • Arranging \(n\) distinct objects around a circle (rotations considered the same): circular permutations.

Key decision: if swapping positions produces a different outcome, the situation is a permutation problem. If order does not matter, the problem is a combination (not the focus here).

Formulas used by a permutation solver

Situation Count Notes
\(r\)-permutations from \(n\) (no repetition) \(\displaystyle nP r=\frac{n!}{(n-r)!}\) Ordered selection of length \(r\) from \(n\) distinct objects.
Permutations with repeated elements \(\displaystyle \frac{n!}{n_1!\,n_2!\cdots n_k!}\) \(n_1,\dots,n_k\) are multiplicities of identical items; \(n=\sum n_i\).
Circular permutations (rotations identical) \(\displaystyle (n-1)!\) Fix one object as an anchor to remove rotational duplicates.

Worked examples (step-by-step)

Example 1: \(nP r\) without repetition

An ordered list of 3 finalists is chosen from 10 contestants (1st, 2nd, 3rd are different ranks). Compute the number of outcomes with a permutation solver.

\[ nP r = 10P3 = \frac{10!}{(10-3)!}=\frac{10!}{7!}=10\cdot 9\cdot 8=720. \]

Result: 720 ordered finalist lists.

Example 2: repeated elements (multiset permutation)

Count distinct arrangements of the letters in “LEVEL”. The letters are \(L,L,E,E,V\): \(n=5\) with multiplicities \(n_L=2\), \(n_E=2\), \(n_V=1\).

\[ \text{Distinct permutations}=\frac{5!}{2!\cdot 2!\cdot 1!} =\frac{120}{2\cdot 2}=30. \]

Result: 30 distinct arrangements.

Example 3: circular permutations

Seat 7 distinct people around a round table. Rotations are considered the same seating.

\[ \text{Circular permutations}=(7-1)!=6!=720. \]

Result: 720 circular seatings (up to rotation).

Visualization: why \(nP r\) multiplies choices

The diagram shows \(4P2\): choose the first position from 4 options, then the second position from 3 remaining options. Each path corresponds to one ordered outcome.

1st position 2nd position Ordered pair A B C D B C D A C D A B D A B C (A,B) (A,C) (A,D) (B,A) (B,C) (B,D) (C,A) (C,B) (C,D) (D,A) (D,B) (D,C) Count = \(4\cdot 3=12\) ordered pairs = \(4P2\)
The multiplication \(4\cdot 3\) matches the factorial form \(4P2=\frac{4!}{(4-2)!}\), illustrating how a permutation solver counts ordered selections without repetition.

Checklist for using a permutation solver correctly

  • Order matters? If yes, proceed with permutations.
  • Repetition allowed? If no, use \(nP r\); if identical items exist, use the multiset formula.
  • Circular arrangement? If rotations are identical, use \((n-1)!\).
  • Final validation: units are “arrangements” or “ordered outcomes,” not probabilities (unless divided by a sample space later).
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