Combinations vs. Permutations

A combination represents the number of ways to choose r items from n total items where the order doesn't matter. If order becomes relevant—such as arranging people in specific positions—you're working with permutations instead.

The key distinction: selecting 3 people from 10 for a committee gives one combination, but arranging those same 3 people into president, vice-president, and treasurer roles produces multiple permutations. Combinations ignore sequence; permutations depend on it.

In practical terms:

  • Combinations: "Which 5 lottery numbers did I pick?" (order irrelevant)
  • Permutations: "What was the winning sequence?" (order critical)

Combination Formula

The standard combination formula calculates selections without repetition. When items can be chosen multiple times, a modified formula accounts for the increased possibilities.

C(n,r) = n! ÷ (r! × (n − r)!)

C(n,r) with repetition = (r + n − 1)! ÷ (r! × (n − 1)!)

  • n — Total number of distinct objects available
  • r — Number of objects you want to select
  • ! — Factorial: the product of all positive integers up to that number (e.g., 5! = 5 × 4 × 3 × 2 × 1 = 120)

Common Pitfalls and Considerations

Understanding when and how to apply combination formulas prevents calculation mistakes.

  1. Confusing combinations with permutations — Many people mistakenly use permutation formulas when order is irrelevant. For selecting 5 committee members from 20 candidates, use combinations—not permutations. The permutation result will be 24 times larger because it treats different orderings as distinct outcomes.
  2. Forgetting to account for repetition rules — Standard combinations assume each item can only be selected once. If you're choosing with replacement—like picking coloured balls returned to the urn each time—use the repetition formula instead. Ignoring this distinction produces dramatically different answers.
  3. Handling large factorials — Factorials grow extremely fast: 20! exceeds 2 trillion. Most calculators express results in scientific notation (mantissa and exponent) to avoid display overflow. A result like 1.23 × 10^15 means 1,230,000,000,000,000 exact combinations.
  4. Verifying when n equals r — When selecting all items (r = n), there is exactly one combination. This often surprises users, but it makes sense: there's only one way to choose everything. The formula correctly produces C(n,n) = 1 in all cases.

Worked Example: 5-Letter Combinations

Suppose you need to find how many distinct 5-letter combinations exist using the 26-letter English alphabet.

Step 1: Identify your variables. n = 26 (total letters), r = 5 (letters per combination).

Step 2: Apply the formula without repetition:

C(26,5) = 26! ÷ (5! × 21!) = 65,780

Step 3: Interpret the result. There are 65,780 unique 5-letter groupings. If repetition were allowed (selecting the same letter multiple times), the formula yields 142,506 combinations—roughly double.

Most practical problems involve selections without repetition: lottery draws, committee formation, or test question selection. Repetition models apply mainly to sampling-with-replacement scenarios or password generation.

Frequently Asked Questions

What's the difference between combinations with and without repetition?

Without repetition, each item from your set can be chosen at most once—like drawing lottery balls without replacing them. With repetition, items return to the pool after selection, allowing duplicates. For instance, choosing 2 letters from A, B, C without repetition yields 3 combinations: AB, AC, BC. With repetition, you add AA, BB, CC, and other duplicates, totalling 6 combinations. The repetition formula produces larger numbers because more options become available.

How many 4-digit combinations are possible from digits 0–9?

Without repetition: C(10,4) = 210 combinations. With repetition: 715 combinations. Note these are combinations (unordered selections), not permutations. If you care about the sequence—say, forming a 4-digit PIN where 1234 differs from 4321—permutations produce 5,040 (without repetition) or 10,000 (with repetition) possibilities. Passwords typically use permutations since sequence matters.

Why does C(12,12) equal 1?

When you select all items from your set, there's exactly one way to do it. C(12,12) = 12! ÷ (12! × 0!) = 1 ÷ 1 = 1. This applies universally: C(n,n) always equals 1. It reflects the logical truth that there's only one combination containing all elements. Conversely, C(n,0)—selecting nothing—also equals 1 for the same reason.

When should I use the combination calculator instead of calculating by hand?

For small values (n and r under 10), hand calculation using the factorial formula is feasible. Beyond that, factorials balloon rapidly—13! alone exceeds 6 billion. Calculators handle large numbers, prevent arithmetic errors, and instantly provide results in scientific notation when needed. For practical problems involving lottery draws, team selections, or probability analysis, a calculator saves time and ensures accuracy.

What if I need permutations instead of combinations?

Permutations factor in the order of selection. Use the permutation formula P(n,r) = n! ÷ (n − r)! for unordered scenarios. For example, selecting 3 people from 10 yields C(10,3) = 120 combinations but P(10,3) = 720 permutations because each 3-person group can be arranged in 6 different sequences. Choose permutations when positions matter: prize placement, seating arrangements, or password sequences.

Can combinations exceed factorials in size?

No. Combinations are always smaller than or equal to their corresponding permutations. C(n,r) ≤ P(n,r) because permutations count every ordering, while combinations treat all orderings of the same items as identical. The ratio between them is exactly r!, the number of ways to arrange r items. So P(n,r) = C(n,r) × r!. This relationship holds universally across all valid inputs.

More statistics calculators (see all)