Kombinationsrechner

Der Kombinationsrechner berechnet C(n, k) — die Anzahl der unterschiedlichen Teilmengen der Größe k, die aus einer Menge von n Elementen gezogen werden. Die Formel: C(n, k) = n! / (k! × (n−k)!), oft geschrieben als 'n wähle k' oder als Binomialkoeffizient. Verwenden Sie diesen, wenn die MENGE der ausgewählten Elemente wichtig ist, aber ihre Reihenfolge nicht (eine Pokerhand, ein Lotterieschein, ein Komitee).

Try a worked example

Combinations vs permutations. Combinations count selections where order DOESN'T matter (a 5-card hand is the same regardless of how it was dealt). Permutations count arrangements where order MATTERS (gold-silver-bronze finish). C(n, k) is always less than P(n, k) by a factor of k!.

Anwendung

  1. 1

    Geben Sie n ein — die Gesamtzahl der verschiedenen verfügbaren Elemente.

  2. 2

    Geben Sie k ein — die Anzahl der Elemente, die Sie auswählen (k muss ≤ n sein).

  3. 3

    C(n, k) erscheint sofort zusammen mit der Formel und einer formatierten Zahl mit Tausendertrennzeichen.

  4. 4

    Für sehr große Ausgaben (>30 Stellen) wechselt der Rechner zur wissenschaftlichen Notation.

  5. 5

    Tippen Sie auf ein Beispiel, um klassische Probleme zu laden (Pokerhände, Lotterien, Komitees).

Häufig gestellte Fragen

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What is a combination?

A combination is a selection of items from a larger set where the order of selection doesn't matter. If you're picking 3 books to take on vacation from a shelf of 10, the trio {Crime and Punishment, Dune, The Hobbit} is the same combination as {Dune, The Hobbit, Crime and Punishment} — same three books, you don't care which order you grabbed them in.

The number of distinct combinations of k items chosen from n items is given by the formula:

C(n, k) = n! / (k! × (n − k)!)

Pronounced "n choose k" and sometimes written as a vertical pair (n on top, k on bottom) inside parentheses. The same number is also called the binomial coefficient — it's the coefficient of xᵏ when you expand (1 + x)ⁿ. The numbers in Pascal's triangle are all binomial coefficients.

How to use the combination calculator

  1. Enter n — the total number of items you can choose from.
  2. Enter k — the size of the subset you're choosing. k must be between 0 and n inclusive.
  3. The result C(n, k) appears instantly with the formula displayed and a thousands-separator-formatted number.
  4. For very large outputs (more than 30 digits), the calculator switches to scientific notation.
  5. Tap a worked example to load classic combination problems — poker hands, lottery odds, committee selections.

Combinations vs permutations — the deciding question

Always ask: does the order matter?

  • YES, order matters → permutations. Gold-Silver-Bronze ≠ Bronze-Silver-Gold. Use P(n, k).
  • NO, order doesn't matter → combinations. {A, B, C} = {C, B, A}. Use C(n, k).

The relationship: C(n, k) = P(n, k) / k!. Combinations are always smaller than permutations by a factor of k! — because each combination corresponds to k! different orderings, all of which collapse into the same combination. C(5, 3) = 10; P(5, 3) = 60 = 10 × 3! = 10 × 6.

Worked examples

Example 1 — Pick 3 books from 5

You have 5 books and want to pick 3 to take on a trip. How many different sets of 3 are possible?

C(5, 3) = 5! / (3! × 2!) = 120 / 12 = 10. Just 10 distinct trios — the order you grab them doesn't matter, only which 3 you end up with.

Example 2 — 5-card poker hands

From a standard 52-card deck, how many different 5-card hands are possible?

C(52, 5) = 2,598,960. About 2.6 million distinct hands. The order you're dealt the cards doesn't matter (a royal flush is a royal flush regardless of which order the cards came out). All of poker probability builds on this number.

Example 3 — UK Lotto: 6 of 49

The UK Lotto requires you to pick 6 numbers from 1-49. How many tickets are needed to cover every combination?

C(49, 6) = 13,983,816. Nearly 14 million combinations. At £2 per ticket, buying every combination would cost about £28 million — far more than the typical jackpot. The "you can guarantee a win by buying every ticket" strategy only works on much smaller lotteries.

Example 4 — Committee selection

You need to pick a 3-person committee from 10 candidates. How many different committees can you form?

C(10, 3) = 120. The order doesn't matter — Alice, Bob, and Carol form the same committee whether you list them in any order. (If you were assigning specific roles like Chair, Vice-Chair, Treasurer, you'd want permutations: P(10, 3) = 720.)

Example 5 — Powerball white balls

The US Powerball draws 5 white balls from 1-69, plus a separate red ball from 1-26. The white-ball portion alone:

C(69, 5) = 11,238,513. About 11.2 million white-ball combinations. Multiply by 26 red-ball options = 292,201,338 total tickets. The "1 in 292 million" odds you hear quoted for Powerball jackpot wins comes directly from this multiplication.

The symmetry property: C(n, k) = C(n, n−k)

An elegant fact: choosing k items to KEEP from n is the same as choosing (n−k) items to DISCARD. Every selection has a complementary selection of the same kind, so the count must be the same.

  • C(10, 3) = C(10, 7) = 120
  • C(52, 5) = C(52, 47) = 2,598,960
  • C(100, 1) = C(100, 99) = 100

The calculator exploits this internally — when computing C(100, 99), it actually computes C(100, 1) = 100, which is far faster (1 multiplication vs 99). This is why the tool can handle n up to 1000 without slowing down.

Pascal's triangle — combinations on display

Pascal's triangle is a visual layout of every C(n, k):

            1                  ← C(0, 0)
          1   1                ← C(1, 0), C(1, 1)
        1   2   1              ← C(2, 0), C(2, 1), C(2, 2)
      1   3   3   1            ← C(3, k)
    1   4   6   4   1          ← C(4, k)
  1   5   10  10  5   1        ← C(5, k)
1   6  15  20  15   6   1      ← C(6, k)

Each row n contains C(n, 0), C(n, 1), ..., C(n, n). Each entry equals the sum of the two entries directly above it (the "Pascal's rule": C(n+1, k+1) = C(n, k) + C(n, k+1)). The triangle is symmetric (C(n, k) = C(n, n−k)) and the row sums are powers of 2 (the sum of row n equals 2ⁿ).

Combinations with repetition

The basic C(n, k) formula assumes WITHOUT repetition — each item appears in your subset at most once. If items can repeat (like choosing 3 ice cream scoops from 5 flavors where you can pick chocolate twice), the formula changes:

C with repetition = C(n + k − 1, k)

Choosing 3 scoops from 5 flavors (repeats allowed): C(5 + 3 − 1, 3) = C(7, 3) = 35.

This calculator uses the no-repetition formula. For with-repetition problems, compute C(n + k − 1, k) using the same calculator with adjusted n.

Where combinations show up

Lottery odds

Every "pick X numbers from Y" lottery is a combination problem. Mega Millions: pick 5 from 70 (C(70, 5) = 12.1M) plus 1 from 25 = 302.5M total combinations. The math is what determines the headline jackpot odds.

Poker probability

Royal flush: 4 ways out of 2,598,960 hands = 1 in 649,740. Straight flush: 36 / 2.6M = 1 in 72,193. Every hand probability is "favorable combinations / total combinations."

Sports brackets

NCAA March Madness Round of 64 → 32: choosing which 32 teams advance from any 64 = C(64, 32) ≈ 1.83 × 10¹⁸ possibilities (but only 2³² = 4.3B if order in the bracket doesn't matter). Every bracket-pool participant is sampling one of these.

Combinatorial chemistry

Drug screening: from a library of 1000 candidate molecules, how many 5-molecule cocktails could you test? C(1000, 5) = 8.25 × 10¹². This is why brute-force combinatorial drug discovery requires careful pruning — the search space is enormous.

Committee and team formation

Workplace teams, jury selection, study groups — anywhere you select a subset of people for a role-undifferentiated task is a combination problem.

Statistics and probability

Binomial distributions, hypergeometric distributions, sampling without replacement — all use combinations as their counting building block.

Special cases worth knowing

  • C(n, 0) = 1 — there's exactly one way to choose nothing (the empty set).
  • C(n, n) = 1 — exactly one way to choose all items.
  • C(n, 1) = n — choose just one of n items, n ways.
  • C(n, n−1) = n — by symmetry with C(n, 1).
  • C(2k, k) = the central binomial coefficient — peak of row 2k in Pascal's triangle, often the largest value in the row.

Common mistakes

  • Confusing C with P. The single most common error in combinatorics. Always ask "does the order matter?" If yes, use permutations.
  • Forgetting the (n−k)! in the denominator. The full formula has n! / (k! × (n−k)!) — three factorials, not two. Easy to drop one when scribbling on paper.
  • Thinking C(n, k) and P(n, k) are interchangeable for "small" k. They're never the same (except trivially when k = 0 or k = 1). Always check what the question is asking.
  • Using the no-repetition formula when items can repeat. A vending machine with 5 buttons where you press 3 (repeats allowed) gives 5³ = 125 outcomes (ordered with repetition), or C(7, 3) = 35 (unordered with repetition), NOT C(5, 3) = 10.
  • Confusing 'combination lock' with combinatorial combinations. A combination lock requires the right SEQUENCE of numbers — that's a permutation, not a combination. A 3-digit lock with 40 positions has 40³ = 64,000 sequences (with repetition), not C(40, 3).

What the calculator gives you, summarized

  • Exact C(n, k) — computed via BigInt for precision up to n = 1000.
  • Thousands-separator formatting — for results small enough to display normally, with commas (US-style) for readability.
  • Scientific approximation — for results with more than ~30 digits, displayed as m × 10ᵉ.
  • Formula display — n! / (k! × (n−k)!) shown with your numbers plugged in.
  • Worked examples — poker hands, UK Lotto, Powerball white balls, and committee picks all loadable with one tap.
  • Combinations-vs-permutations callout — the most-confused topic in combinatorics, called out inline.

Two inputs (n and k), one BigInt-precise output. The math is just division of factorials, but the answers explain everything from poker odds to bracket pools to lottery probabilities.