9.1 Fundamental Counting Principle, Permutations & Combinations

9.1 Fundamental Counting Principle, Permutations & Combinations

Combinatorics—the mathematical branch devoted to counting, arranging, and grouping sets of elements—forms the foundation of probability theory, statistics, and discrete mathematics. On the CLEP College Mathematics examination, Counting and Probability represents 10% of the total blueprint (~6 questions).

Mastering the Fundamental Counting Principle, Permutations (where order matters), and Combinations (where order does not matter) allows candidates to solve both routine computational problems and complex, multi-stage non-routine word problems rapidly and accurately.

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1. The Fundamental Counting Principle (FCP)

The Fundamental Counting Principle (Multiplication Principle of Counting) establishes that when an experiment or process consists of a sequence of separate, independent stages, the total number of possible composite outcomes equals the product of the number of choices available at each individual stage.

+-----------------------------------------------------------------------------+
|                   THE FUNDAMENTAL COUNTING PRINCIPLE (FCP)                  |
|                                                                             |
|   Stage 1 ---------> Stage 2 ---------> Stage 3 ---------> Stage k         |
|   (n_1 ways)         (n_2 ways)         (n_3 ways)         (n_k ways)       |
|                                                                             |
|            TOTAL COMPOSITE OUTCOMES = n_1 * n_2 * n_3 * ... * n_k           |
+-----------------------------------------------------------------------------+

Mathematical Formalization

If a composite task consists of $k$ successive steps such that:

• Step 1 can be performed in $n_1$ ways,
• Step 2 can be performed in $n_2$ ways (regardless of the outcome of Step 1),
• Step 3 can be performed in $n_3$ ways,
• $\dots$
• Step $k$ can be performed in $n_k$ ways,

Then the entire sequence of tasks can be executed in exactly:

$N = n_1 \times n_2 \times n_3 \times \dots \times n_k$

Sequential Choices with and Without Repetition

When applying the FCP, you must distinguish between situations where items may be reused (repetition allowed) and situations where each choice removes an item from the candidate pool (repetition not allowed).

Worked Example 1: Vehicle License Plate Configurations

Problem: A state motor vehicle department issues license plates consisting of $3$ letters followed by $3$ numerical digits ($0$ through $9$).

1. How many distinct license plates can be generated if letters and digits can be repeated?
2. How many distinct license plates can be generated if no letter and no digit may be repeated?
3. How many distinct license plates can be generated if repetition is allowed, but the first letter cannot be 'Q' or 'Z', and the first digit cannot be $0$?

Solution Walkthrough:

1. With Repetition Allowed:
   • There are $26$ options for each of the $3$ letter positions, and $10$ options ($0$–$9$) for each of the $3$ digit positions.
   • $N = 26 \times 26 \times 26 \times 10 \times 10 \times 10 = 26^3 \times 10^3 = 17{,}576 \times 1{,}000 = 17{,}576{,}000$.
2. Without Repetition (Distinct Characters):
   • Letter positions decrease: $26 \times 25 \times 24 = 15{,}600$.
   • Digit positions decrease: $10 \times 9 \times 8 = 720$.
   • $N = 15{,}600 \times 720 = 11{,}232{,}000$.
3. With Specific Restrictions:
   • First letter: $26 - 2 = 24$ choices. Second and third letters: $26$ choices each.
   • First digit: $10 - 1 = 9$ choices ($1$ through $9$). Second and third digits: $10$ choices each.
   • $N = 24 \times 26 \times 26 \times 9 \times 10 \times 10 = 16{,}224 \times 900 = 14{,}601{,}600$.

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2. Factorial Arithmetic & Properties

A factorial represents the product of all positive integers less than or equal to a given non-negative integer $n$.

Factorial Definition

For any positive integer $n \in \mathbb{Z}^+$:

$n! = n \times (n-1) \times (n-2) \times \dots \times 3 \times 2 \times 1$

The Special Definition of Zero Factorial ($0! = 1$)

By mathematical definition and combinatorial consistency:

$0! = 1$

Why does $0! = 1$? Combinatorially, $n!$ represents the number of ways to arrange $n$ distinct objects in a line. There is exactly $1$ way to arrange zero objects (the empty arrangement). Algebraically, applying the recurrence relation $(n-1)! = \frac{n!}{n}$ for $n=1$ yields $0! = \frac{1!}{1} = 1$.

Common Factorial Values for Quick Recall

Cancelling Factorials in Algebraic Quotients

Never evaluate large factorials completely before dividing. Always expand the larger factorial down to the index of the smaller factorial and cancel common factors:

$\frac{10!}{7! \times 3!} = \frac{10 \times 9 \times 8 \times 7!}{7! \times (3 \times 2 \times 1)} = \frac{10 \times 9 \times 8}{6} = \frac{720}{6} = 120$

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3. Permutations (Order Matters)

A permutation is an ordered arrangement of $r$ objects selected from a total set of $n$ distinct objects without replacement. Whenever the sequence, ranking, position, or specific title assigned to selected items matters, the problem requires permutations.

+-----------------------------------------------------------------------------+
|                           PERMUTATION MECHANICS                             |
|                                                                             |
|   - Total Pool: n distinct items                                            |
|   - Selection Size: r items chosen without replacement                      |
|   - Core Condition: ORDER / RANKING MATTERS                                 |
|                                                                             |
|                     Formula: nPr = n! / (n - r)!                            |
+-----------------------------------------------------------------------------+

The Permutation Formula

$_n P_r = P(n, r) = \frac{n!}{(n-r)!} = n \times (n-1) \times (n-2) \times \dots \times (n - r + 1)$

Where:

• $n$ = Total number of available distinct items in the pool
• $r$ = Number of items being selected and arranged ($0 \le r \le n$)
• $(n-r)!$ = The unselected items eliminated from the arrangement

Special Boundary Cases for Permutations

• Permuting all $n$ items: $_n P_n = \frac{n!}{(n-n)!} = \frac{n!}{0!} = \frac{n!}{1} = n!$
• Permuting a single item: $_n P_1 = \frac{n!}{(n-1)!} = n$
• Permuting zero items: $_n P_0 = \frac{n!}{(n-0)!} = \frac{n!}{n!} = 1$

Worked Example 2: Elected Officers

Problem: A regional student council consists of $12$ voting members. The council must elect a President, a Vice President, a Secretary, and a Treasurer. In how many different ways can these $4$ executive officer positions be filled assuming no member can hold more than one office?

Solution:

• Because the $4$ positions carry distinct titles and specific roles, the order of selection matters. This is a permutation of $n = 12$ items taken $r = 4$ at a time.
• Substitute into the permutation formula: $_{12} P_4 = \frac{12!}{(12-4)!} = \frac{12!}{8!} = 12 \times 11 \times 10 \times 9 = 11{,}880$
• Conclusion: There are $11{,}880$ unique executive officer slates possible.

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4. Specialized Permutations: Duplicates & Circular Arrangements

Permutations with Indistinguishable (Duplicate) Elements

When arranging a collection of $n$ items where some items are identical (indistinguishable duplicates), standard factorial $n!$ overcounts arrangements that look identical. We divide $n!$ by the factorial of each duplicate group's frequency.

Indistinguishable Permutation Formula

If a set contains $n$ total items where $n_1$ are of type 1, $n_2$ are of type 2, $\dots$, and $n_k$ are of type $k$ (with $n_1 + n_2 + \dots + n_k = n$), the number of distinct linear permutations is:

$N = \frac{n!}{n_1! \times n_2! \times n_3! \times \dots \times n_k!}$

Worked Example 3: Word Anagrams

Problem: How many distinct 11-letter arrangements can be formed using all the letters in the word MISSISSIPPI?

Solution:

1. Count total letters: $n = 11$.
2. Group and count identical letters:
   • M: $1$
   • I: $4$
   • S: $4$
   • P: $2$
   • Check: $1 + 4 + 4 + 2 = 11$.
3. Apply the duplicate permutation formula: $N = \frac{11!}{1! \times 4! \times 4! \times 2!} = \frac{39{,}916{,}800}{1 \times 24 \times 24 \times 2} = \frac{39{,}916{,}800}{1{,}152} = 34{,}650$

• Conclusion: Exactly $34{,}650$ distinct anagrams can be formed.

Circular Permutations

When arranging $n$ distinct objects in a circle rather than a straight line, linear shifts that merely rotate all participants around the table without changing their relative neighbors do not create new arrangements. Because there is no fixed "first" position, fixing one reference person leaves $(n-1)$ remaining positions to arrange.

Circular Permutation Formulas

• Standard Circular Permutations (Directional / Front-to-Back Oriented): $P_{\text{circle}} = (n - 1)!$
• Reflective Circular Permutations (Key rings, beaded necklaces with reversible faces): $P_{\text{necklace}} = \frac{(n - 1)!}{2}$

Worked Example 4: Circular Seating

Problem: In how many distinct ways can $6$ conference delegates be seated around a circular discussion table?

Solution:

• Apply the circular permutation formula: $P = (6 - 1)! = 5! = 5 \times 4 \times 3 \times 2 \times 1 = 120$ ways.

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5. Combinations (Order Does NOT Matter)

A combination is an unordered collection or subset of $r$ objects selected from a set of $n$ distinct objects without replacement. When the order, sequence, or internal arrangement of the selected items does not affect the outcome, the problem requires combinations.

+-----------------------------------------------------------------------------+
|                           COMBINATION MECHANICS                             |
|                                                                             |
|   - Total Pool: n distinct items                                            |
|   - Selection Size: r items chosen without replacement                      |
|   - Core Condition: ORDER DOES NOT MATTER (Equal Group Status)              |
|                                                                             |
|                 Formula: nCr = binom(n, r) = n! / [r! * (n - r)!]           |
+-----------------------------------------------------------------------------+

The Combination Formula

$_n C_r = \binom{n}{r} = C(n, r) = \frac{n!}{r!(n-r)!} = \frac{_n P_r}{r!}$

Where:

• $n$ = Total available distinct items
• $r$ = Number of items selected to form the subset
• $r!$ in the denominator eliminates the $r!$ internal permutations of the selected subgroup

Fundamental Properties of Combinations

1. Reflection Symmetry: Selecting $r$ items to include from a pool of $n$ is mathematically equivalent to selecting $(n-r)$ items to leave out: $\binom{n}{r} = \binom{n}{n-r}$ Example: $\binom{15}{13} = \binom{15}{2} = \frac{15 \times 14}{2 \times 1} = 105$.
2. Boundary Values: $\binom{n}{0} = 1, \quad \binom{n}{n} = 1, \quad \binom{n}{1} = n, \quad \binom{n}{n-1} = n$

Multi-Group Combinations (Compound Selections)

When a problem requires choosing subsets from multiple distinct categories, compute the combinations for each category separately and multiply them using the Fundamental Counting Principle.

Worked Example 5: Multi-Group Committee Selection

Problem: A corporate board consists of $9$ accountants and $7$ engineers. A specialized audit committee of $5$ members must be formed consisting of exactly $3$ accountants and $2$ engineers. In how many different ways can this committee be selected?

Solution:

1. Calculate the number of ways to choose $3$ accountants from $9$: $\binom{9}{3} = \frac{9!}{3!(9-3)!} = \frac{9 \times 8 \times 7}{3 \times 2 \times 1} = \frac{504}{6} = 84$
2. Calculate the number of ways to choose $2$ engineers from $7$: $\binom{7}{2} = \frac{7!}{2!(7-2)!} = \frac{7 \times 6}{2 \times 1} = \frac{42}{2} = 21$
3. Multiply the independent stage combinations using the Fundamental Counting Principle: $\text{Total Committees} = \binom{9}{3} \times \binom{7}{2} = 84 \times 21 = 1{,}764$

Worked Example 6: The Handshake Problem

Problem: At a professional networking summit, $15$ attendees meet. If every attendee shakes hands exactly once with every other attendee, how many total handshakes occur?

Solution:

• A handshake requires selecting an unordered pair of $2$ people from the pool of $15$. Order does not matter (Person A shaking Person B's hand is identical to Person B shaking Person A's hand).
• Evaluate $\binom{15}{2}$: $\binom{15}{2} = \frac{15 \times 14}{2 \times 1} = \frac{210}{2} = 105 \text{ handshakes}$

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6. Permutations vs. Combinations: Decision Matrix

+-----------------------------------------------------------------------------+
|                  PERMUTATIONS VS. COMBINATIONS DECISION MATRIX              |
|                                                                             |
|   CRITERIA               PERMUTATIONS (_n P_r)     COMBINATIONS (_n C_r)    |
|   --------------------   -----------------------   ----------------------   |
|   Order / Sequence       MATTERS                   DOES NOT MATTER          |
|   Group Hierarchy        Distinct roles / titles   Equal status / uniform   |
|   Denominator Factor     (n - r)! only             r! * (n - r)!            |
|   Relative Size          Larger value              Smaller value            |
|                                                                             |
|   COMMON EXAM CONTEXTS:                                                     |
|   - Permutations:        Elected officers (Pres/VP), race ranks (1st/2nd),  |
|                          passwords/PINs, seating in a line, batting order.  |
|   - Combinations:        Committees, delegations, card hands, handshakes,   |
|                          selecting lottery balls, pizza toppings.           |
+-----------------------------------------------------------------------------+

The Litmus Test for Word Problems

To determine whether to use $_n P_r$ or $_n C_r$ on the CLEP exam, ask yourself:

"If I swap the order of any two selected items, does it create a completely new, distinct outcome?"

• YES $\implies$ Permutation ($_n P_r$)
• NO $\implies$ Combination ($_n C_r$)

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7. TI-30XS MultiView Calculator Execution Guide

All factorial, permutation, and combination functions on the TI-30XS MultiView calculator reside within the [prb] (Probability) Menu.

+-----------------------------------------------------------------------------+
|                   TI-30XS MULTIVIEW PROBABILITY KEYSTROKES                  |
|                                                                             |
|   1. PERMUTATIONS (_n P_r):                                                 |
|      Input: n  ->  Press [prb]  ->  Select 1:nPr  ->  Input r  ->  [enter]  |
|                                                                             |
|   2. COMBINATIONS (_n C_r):                                                 |
|      Input: n  ->  Press [prb]  ->  Select 2:nCr  ->  Input r  ->  [enter]  |
|                                                                             |
|   3. FACTORIAL (n!):                                                        |
|      Input: n  ->  Press [prb]  ->  Select 3:!    ->  [enter]               |
+-----------------------------------------------------------------------------+

Quick Keystroke Reference Table

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8. Common CLEP Traps & Strategic Checkpoints

• Trap 1: Defaulting to Permutations for Committees: If a problem asks for a "committee of 4 from 10 people," students often compute $_{10} P_4 = 5{,}040$. Unless specific officer roles (President, Secretary) are defined, committee members share equal status, requiring combinations: $\binom{10}{4} = 210$.
• Trap 2: Forgetting $0! = 1$: In algebraic simplifications like $\frac{n!}{(n-r)!}$ when $n = r$, the denominator becomes $0! = 1$, NOT $0$. Division by zero does not occur.
• Trap 3: Adding Instead of Multiplying Independent Stages: In multi-group selections (e.g., choosing accountants AND engineers), multiply the combinations together ($\binom{9}{3} \times \binom{7}{2}$). Adding them is only valid when choosing accountants OR engineers (mutually exclusive alternatives).
• Trap 4: Missing Indistinguishable Letters: When calculating anagrams of words with repeated letters (like ALABAMA or COMMITTEE), forgetting to divide by the duplicate factorials yields drastically inflated, incorrect answers.