Counting: Permutations & Combinations
Three friends and two tickets, and a single quiet question — does the order matter? From that one question the whole of counting opens up: the multiplication rule, permutations, and combinations, each traced on small numbers you can hold.
What you'll learn
- The multiplication rule: choices made in sequence multiply
- Permutations nPr = n!/(n-r)! — ordered arrangements, slot by slot
- Combinations nCr = n!/(r!(n-r)!) — order forgotten by dividing by r!
- Arrangements with repeats, and why nCr is the backbone of the binomial
Before you start
Three friends — Atharv, Diya, and Kabir — have two cinema tickets to share. Who gets to go? You can simply name the pairs: Atharv and Diya, Atharv and Kabir, Diya and Kabir. Three pairs, found by hand in a moment.
Now make it ten friends and three tickets. Listing every group by hand is suddenly hopeless — there are far too many, and you would lose count halfway. So we need a way to count the groupings without writing them all out. And before we count anything, one quiet question decides which kind of counting we do: does the order matter?
The one question that splits everything
Sharing tickets, order does not matter. A pair of friends is the same pair whoever you happen to name first. But suppose the two tickets were numbered — seat 1 and seat 2 — and it mattered who sat where. Then Atharv in seat 1, Diya in seat 2 is a different outcome from Diya in seat 1, Atharv in seat 2. The same two people, counted as two, because the order changed.
That single difference splits all of counting in two. Hold on to it; everything below is just this question, answered carefully.
Counting by filling slots
Let us count the numbered-seat version first, because it is the more natural one.
Think of the two numbered seats as two slots to fill, in order. Seat 1 can go to
any of the three friends — three choices. Once seat 1 is taken, seat 2 can go to
either of the two who remain — two choices. For each of the three ways to fill
seat 1 there are two ways to fill seat 2, so the seats can be filled in
3 × 2 = 6 ways.
That is the whole of the multiplication rule: choices made in sequence
multiply. A five-question test with four options each is five slots of four, so it
can be answered in 4 × 4 × 4 × 4 × 4 = 4⁵ = 1024 ways. Same idea, more slots.
Permutations — when order matters
Those six ordered seatings have a name. Arranging r things out of n, in order,
is a permutation, written nPr. The slots shrink as you fill them — n
choices, then n−1, then n−2, down to the last slot — so
nPr = n · (n−1) · … · (n−r+1) = n! / (n−r)!
For our friends, 3P2 = 3 · 2 = 6, exactly the six seatings we just counted. The
factorial form n!/(n−r)! is only bookkeeping; the shrinking slots are the real
idea.
Combinations — when order does not matter
But the cinema tickets were never numbered. A pair is a pair. So among those six
ordered seatings, each pair of friends was counted twice — once for each order
the two could sit in. To forget the order, divide the six by the two orderings of
each pair: 6 / 2 = 3. Three pairs — exactly the list we made by hand at the very
start.
Selecting r things out of n when order does not matter is a combination,
written nCr. It is the permutation with each group’s r! internal orderings
collapsed to one:
nCr = nPr / r! = n! / ( r! · (n−r)! )
So 3C2 = 6 / 2! = 3. And now the ten-friends question is no trouble. Numbered
tickets: 10P3 = 10 · 9 · 8 = 720. An unnumbered group of three:
10C3 = 720 / 3! = 720 / 6 = 120. No listing required.
Two small facts fall out and are worth keeping. nC0 = nCn = 1 — there is exactly
one way to choose nobody, and one way to choose everybody. And nCr = nC(n−r),
because choosing which r to include is the same as choosing which n−r to leave
out; this quietly turns 25C23 into the one-line 25C2 = 300.
When some items are identical
One more case, because GATE likes it. When the things being arranged are not all
different, some orderings look the same and must not be counted twice. Arranging
n items where one value repeats n₁ times, another n₂ times, and so on:
arrangements = n! / ( n₁! · n₂! · … )
The letters of LEVEL — two L’s, two E’s, one V — arrange in
5! / (2! · 2!) = 120 / 4 = 30 distinct words, not 5! = 120, because swapping
the two L’s (or the two E’s) leaves the word unchanged. Same move as the
combination: divide out the orderings you cannot tell apart.
A worked example — counting hidden inside a probability
Most “probability” questions in this band are really a counting question wearing a disguise: favourable outcomes over total outcomes. Watch both counts.
total PINs (repeats allowed) = 10 · 10 · 10 · 10 = 10⁴ = 10000
all four digits different = 10 · 9 · 8 · 7 = 10P4 = 5040
P(all different) = 5040 / 10000 = 0.504
Just over one-half. The numerator is a permutation — the four positions are ordered — and the denominator is the plain multiplication rule. Get the two counts right and the probability is a single division.
A question to carry forward
Soon you will meet the binomial distribution, where the number of ways to get k
heads in n coin tosses is exactly nCk — a combination, not a permutation. Here
is the thread to pull: the tosses happen in a definite order, so why does the order
of the heads not matter when we count them?
In one breath
- One question splits all of counting: does order matter?
- Multiplication rule: choices in sequence multiply — fill slots (
4⁵ = 1024). - Permutation
nPr = n!/(n−r)!— ordered; slots shrinkn, n−1, …(3P2 = 6,10P3 = 720). - Combination
nCr = n!/(r!(n−r)!)— unordered; it isnPrwith each group’sr!orderings merged into one (3C2 = 3,10C3 = 120). - Repeats: divide by the factorial of each repeat count (
LEVEL → 5!/(2!2!) = 30); andnCr = nC(n−r). - Counting is the engine of easy probability questions (distinct PIN
= 5040/10000 = 0.504), andnCris the backbone of the binomial.
Practice
Quick check
Practice this in an interview
All questionsPermutations count ordered arrangements: P(n,k) = n!/(n-k)!. Combinations count unordered selections: C(n,k) = n!/[k!(n-k)!]. The rule is simple — if the order of selection matters, permute; if it doesn't, combine. Combinations are always smaller by a factor of k!.
Each distribution has a natural generative story: Bernoulli is a single coin flip; Binomial sums Bernoullis; Poisson counts rare arrivals; Normal emerges from sums of many small effects; Exponential models waiting times between Poisson events; Uniform assigns equal probability across a range. Choosing correctly comes from matching that story to the data-generating process.
The law of total probability decomposes P(A) over a mutually exclusive, exhaustive partition of the sample space: P(A) = Σ P(A|Bᵢ)·P(Bᵢ). It is the engine behind the Bayes denominator and any calculation where you want an overall rate built from segment-level rates.
Binomial counts successes in a fixed number of independent trials with a fixed success probability. Poisson counts events in a continuous interval when events are rare and arrive independently at a constant average rate. Poisson is the limiting case of Binomial as n → ∞ and p → 0 with np = λ fixed.