Binomial Theorem, Pascal & Combinatorial Identities

Study Sheet

Binomial Theorem, Pascal & Combinatorial Identities

Competition counting & probability, Unit 4

The Binomial Theorem & Specific Coefficients

Concept
The Binomial Theorem

For any nonnegative integer nn,

(x+y)n=k=0n(nk)xnkyk.(x+y)^n=\sum_{k=0}^{n}\binom{n}{k}x^{\,n-k}\,y^{\,k}.

The coefficient (nk)\binom{n}{k} is called a binomial coefficient. The term containing yky^k (and hence xnkx^{n-k}) is

(nk)xnkyk.\binom{n}{k}x^{\,n-k}y^{\,k}.

Why it is true (combinatorial view): expanding (x+y)n=(x+y)(x+y)(x+y)n(x+y)^n=\underbrace{(x+y)(x+y)\cdots(x+y)}_{n} means choosing, from each of the nn factors, either xx or yy. A term xnkykx^{n-k}y^k arises from every way of choosing yy in exactly kk of the factors, and there are (nk)\binom{n}{k} such choices.

Reminder — The binomial theorem:(x+y)n=k=0n(nk)xnkyk(x+y)^{n}=\sum_{k=0}^{n}\binom{n}{k}x^{\,n-k}y^{k}
Example
Worked example: a specific coefficient

Find the coefficient of x5x^{5} in (2x3)8(2x-3)^{8}.

The general term is (8k)(2x)8k(3)k=(8k)28k(3)kx8k\binom{8}{k}(2x)^{8-k}(-3)^{k}=\binom{8}{k}2^{8-k}(-3)^{k}x^{8-k}. We need 8k=58-k=5, so k=3k=3:

(83)25(3)3=5632(27)=48384.\binom{8}{3}2^{5}(-3)^{3}=56\cdot 32\cdot(-27)=-48384.

So the coefficient of x5x^5 is 48384\boxed{-48384}.

Tip

Tips. (1) Match the exponent first, then plug in kk. (2) Track signs carefully: a term like (3)k(-3)^k alternates. (3) For (ax+bx)n\left(ax+\tfrac{b}{x}\right)^n, the general term is (nk)ankbkxn2k\binom{n}{k}a^{n-k}b^{k}x^{n-2k}; set n2kn-2k equal to the desired power.

Pascal's Triangle & Pascal's Rule

Concept
Pascal's Rule
(nk)=(n1k1)+(n1k).\binom{n}{k}=\binom{n-1}{k-1}+\binom{n-1}{k}.

Every interior entry of Pascal's Triangle is the sum of the two entries directly above it. Row nn (starting at n=0n=0) lists (n0),(n1),,(nn)\binom{n}{0},\binom{n}{1},\dots,\binom{n}{n}.

111121133114641\begin{array}{ccccccccc} &&&&1&&&&\\ &&&1&&1&&&\\ &&1&&2&&1&&\\ &1&&3&&3&&1&\\ 1&&4&&6&&4&&1 \end{array}

Combinatorial proof: to form a kk-element committee from nn people, fix one person PP. Either PP is on the committee (choose the other k1k-1 from the remaining n1n-1: (n1k1)\binom{n-1}{k-1} ways) or PP is not (choose all kk from the remaining n1n-1: (n1k)\binom{n-1}{k} ways).

Example
Worked example: using Pascal's Rule

Simplify (94)+(95)\binom{9}{4}+\binom{9}{5}.

By Pascal's Rule with n1=9n-1=9, k=5k=5: (94)+(95)=(105)=252\binom{9}{4}+\binom{9}{5}=\binom{10}{5}=252.

Tip

Tips. Symmetry (nk)=(nnk)\binom{n}{k}=\binom{n}{n-k} mirrors each row. The first nonzero entries are (n0)=1\binom{n}{0}=1 and (n1)=n\binom{n}{1}=n. Memorize rows up to n=6n=6 for speed on contests.

Row Sums & Alternating Sums

Concept
Sum and alternating sum of a row
k=0n(nk)=2n,k=0n(1)k(nk)=0  (n1).\sum_{k=0}^{n}\binom{n}{k}=2^{n},\qquad \sum_{k=0}^{n}(-1)^k\binom{n}{k}=0\ \ (n\ge 1).

Set x=y=1x=y=1 in the Binomial Theorem for the first; set x=1,y=1x=1,\,y=-1 for the second. Combinatorial view of 2n2^n: the total number of subsets of an nn-element set, counted by size, is k(nk)\sum_k\binom{n}{k}; but each element is independently in or out, giving 2n2^n subsets.

Example
Worked example: even-index sum

Evaluate (n0)+(n2)+(n4)+\binom{n}{0}+\binom{n}{2}+\binom{n}{4}+\cdots.

Add the two identities: adding (nk)=2n\sum\binom{n}{k}=2^n and (1)k(nk)=0\sum(-1)^k\binom{n}{k}=0 cancels the odd-index terms and doubles the even ones, so

(n0)+(n2)+=12(2n+0)=2n1.\binom{n}{0}+\binom{n}{2}+\cdots=\tfrac{1}{2}\bigl(2^n+0\bigr)=2^{n-1}.

The odd-index sum equals 2n12^{n-1} as well.

Tip

Tips. Plugging clever values (x=1,1,2,12,x=1,-1,2,\tfrac12,\ldots) into (x+y)n(x+y)^n is the master trick for summing binomial coefficients. To split even/odd indices, average f(1)f(1) and f(1)f(-1).

The Hockey Stick Identity

Concept
Hockey Stick Identity
i=rn(ir)=(n+1r+1).\sum_{i=r}^{n}\binom{i}{r}=\binom{n+1}{r+1}.

Summing a diagonal of Pascal's Triangle (the “stick”) gives the entry just below and to the side of its end (the “blade”). Combinatorial proof: to choose r+1r+1 numbers from {1,2,,n+1}\{1,2,\dots,n+1\}, condition on the largest chosen number i+1i+1. The remaining rr numbers come from {1,,i}\{1,\dots,i\} in (ir)\binom{i}{r} ways; summing over i=r,,ni=r,\dots,n gives the total (n+1r+1)\binom{n+1}{r+1}.

Example
Worked example

Compute (22)+(32)+(42)+(52)+(62)\binom{2}{2}+\binom{3}{2}+\binom{4}{2}+\binom{5}{2}+\binom{6}{2}.

Here r=2r=2, n=6n=6, so the sum is (73)=35\binom{7}{3}=35. (Check: 1+3+6+10+15=351+3+6+10+15=35.)

Tip

Tips. The lower index rr is fixed while the upper index climbs. A common variant, i=0m(r+ii)=(r+m+1m)\sum_{i=0}^{m}\binom{r+i}{i}=\binom{r+m+1}{m}, follows by symmetry.

Vandermonde's Identity

Concept
Vandermonde's Identity
k=0p(mk)(npk)=(m+np).\sum_{k=0}^{p}\binom{m}{k}\binom{n}{p-k}=\binom{m+n}{p}.

Combinatorial proof: to choose a committee of pp people from a group of mm women and nn men, choose kk women and pkp-k men; summing over all valid kk counts every committee exactly once, giving (m+np)\binom{m+n}{p}. The special case m=n=pm=n=p gives k(nk)2=(2nn)\sum_{k}\binom{n}{k}^2=\binom{2n}{n} (using symmetry (nnk)=(nk)\binom{n}{n-k}=\binom{n}{k}).

Example
Worked example

Evaluate k=03(3k)(43k)\sum_{k=0}^{3}\binom{3}{k}\binom{4}{3-k}.

By Vandermonde with m=3,n=4,p=3m=3,\,n=4,\,p=3: the sum is (73)=35\binom{7}{3}=35.

Tip

Tips. Recognize Vandermonde whenever a sum has two binomial factors whose upper indices are constant and whose lower indices add to a constant. The sum-of-squares case (nk)2=(2nn)\sum\binom{n}{k}^2=\binom{2n}{n} appears constantly.

Combinatorial (Committee--Chair) Identities

Concept
The absorption / committee--chair identity
k(nk)=n(n1k1).k\binom{n}{k}=n\binom{n-1}{k-1}.

Combinatorial proof (choose a committee and a chair): count pairs (committee of size kk, a distinguished chair on it). Left side: pick the committee ((nk)\binom{n}{k} ways), then the chair from its kk members. Right side: pick the chair first (nn ways), then the remaining k1k-1 members from the other n1n-1 people. Two useful consequences:

k=0nk(nk)=n2n1,k=0nk2(nk)=n(n+1)2n2.\sum_{k=0}^{n}k\binom{n}{k}=n\,2^{\,n-1},\qquad \sum_{k=0}^{n}k^2\binom{n}{k}=n(n+1)2^{\,n-2}.
Example
Worked example

Evaluate k=0nk(nk)\sum_{k=0}^{n}k\binom{n}{k}.

Replace k(nk)=n(n1k1)k\binom{n}{k}=n\binom{n-1}{k-1}:

k=0nk(nk)=nk=1n(n1k1)=nj=0n1(n1j)=n2n1.\sum_{k=0}^{n}k\binom{n}{k}=n\sum_{k=1}^{n}\binom{n-1}{k-1}=n\sum_{j=0}^{n-1}\binom{n-1}{j}=n\,2^{\,n-1}.
Tip

Tips. The “double counting” strategy---count one set two ways---proves nearly all binomial identities. The absorption identity is also how you turn a weighted sum k(nk)\sum k\binom{n}{k} into a plain row sum.

Lattice Path Counting

Concept
Counting monotonic lattice paths

The number of lattice paths from the origin (0,0)(0,0) to (m,n)(m,n) using only unit steps right (RR) and up (UU) is

(m+nm)=(m+nn).\binom{m+n}{m}=\binom{m+n}{n}.

Each path is a sequence of m+nm+n steps of which exactly mm are RR; choosing which steps are RR determines the path.

Example
Worked example

How many shortest paths go from (0,0)(0,0) to (4,3)(4,3) along grid lines?

Each path uses 44 rights and 33 ups, 77 steps total: (74)=(73)=35\binom{7}{4}=\binom{7}{3}=35 paths. (One such path is drawn above.)

Tip

Tips. Paths through a required point PP multiply: (paths OPO\to P)×\times(paths PP\to end). To avoid a forbidden point, subtract the paths that pass through it. Pascal's Rule is exactly the lattice-path recursion: paths to (m,n)(m,n) = paths to (m1,n)(m-1,n) + paths to (m,n1)(m,n-1).

Going Deeper: Proofs, Generating Functions & Extracting Coefficients

Concept
Three lenses on the same identities

1. Combinatorial (double counting). Count a set of objects two different ways; the two counts must be equal. This proved Pascal's Rule, Hockey Stick, Vandermonde, and the committee--chair identity above.

2. Generating functions. Treat (1+x)n=k(nk)xk(1+x)^n=\sum_k\binom{n}{k}x^k as a polynomial whose coefficients store the binomial coefficients. Multiplying series adds exponents, so identities about sums become statements about products of polynomials. For instance, Vandermonde falls out of

(1+x)m(1+x)n=(1+x)m+n(1+x)^m(1+x)^n=(1+x)^{m+n}

by comparing the coefficient of xpx^p on both sides: the left side gives k(mk)(npk)\sum_k\binom{m}{k}\binom{n}{p-k}, the right gives (m+np)\binom{m+n}{p}.

3. Extracting coefficients. The symbol [xp]F(x)[x^p]F(x) means “the coefficient of xpx^p in FF.” Many contest problems reduce to computing [xp][x^p] of a product of simple factors---exactly the specific-coefficient technique from Section 1.

Example
Worked example: coefficients via a product

Find k=0n(nk)2\sum_{k=0}^{n}\binom{n}{k}^2 using generating functions.

Since (nk)=(nnk)\binom{n}{k}=\binom{n}{n-k}, the sum is k(nk)(nnk)=[xn](1+x)n(1+x)n=[xn](1+x)2n=(2nn).\sum_k\binom{n}{k}\binom{n}{n-k}=[x^n](1+x)^n(1+x)^n=[x^n](1+x)^{2n}=\binom{2n}{n}.

Tip

Big picture. Binomial coefficients live at the crossroads of algebra and counting. Every identity in this unit has a story (count something two ways) and a formula (compare coefficients in a product). When you see a sum of products of binomial coefficients, ask three questions: Is it a row sum? (x=±1x=\pm1) Is it a diagonal? (Hockey Stick) Are two groups being merged? (Vandermonde). And when you need a single coefficient, match the exponent first, then evaluate. Master both the counting story and the algebra, and these problems become routine.

The Roots of Unity Filter

Concept
Extracting an arithmetic slice of a row

Let ω=e2πi/m\omega=e^{2\pi i/m} be a primitive mmth root of unity. The key fact is the orthogonality relation

1mj=0m1ωjt={1if mt,0otherwise.\frac{1}{m}\sum_{j=0}^{m-1}\omega^{jt}= \begin{cases} 1 & \text{if } m\mid t,\\[2pt] 0 & \text{otherwise.} \end{cases}

This average acts as an on/off switch that survives only when the exponent is a multiple of mm. Apply it to the generating polynomial f(x)=(1+x)n=k=0n(nk)xkf(x)=(1+x)^n=\sum_{k=0}^{n}\binom{n}{k}x^k. Substituting x=ωjx=\omega^j, weighting by ωjr\omega^{-jr}, and averaging over jj isolates exactly the terms with kr(modm)k\equiv r\pmod m:

 kr (mod m)(nk)=1mj=0m1ωjr(1+ωj)n. \boxed{\ \sum_{k\equiv r\ (\mathrm{mod}\ m)}\binom{n}{k} =\frac{1}{m}\sum_{j=0}^{m-1}\omega^{-jr}\,(1+\omega^j)^n.\ }

The m=2m=2, r=0r=0 case recovers the even-index sum 2n12^{n-1} from Section 3; the filter is its far-reaching generalization.

Example
Worked example (AIME flavor): every third entry

Evaluate S=(90)+(93)+(96)+(99)=k(93k)S=\displaystyle\binom{9}{0}+\binom{9}{3}+\binom{9}{6}+\binom{9}{9}=\sum_{k}\binom{9}{3k}.

Take m=3m=3, r=0r=0, n=9n=9, and ω=e2πi/3=12+32i\omega=e^{2\pi i/3}=-\tfrac12+\tfrac{\sqrt3}{2}i. The filter gives

S=13[(1+1)9+(1+ω)9+(1+ω2)9].S=\frac{1}{3}\Bigl[(1+1)^9+(1+\omega)^9+(1+\omega^2)^9\Bigr].

Now simplify the two complex factors. Since 1+ω+ω2=01+\omega+\omega^2=0,

1+ω=12+32i=eiπ/3,1+ω2=1232i=eiπ/3.1+\omega=\tfrac12+\tfrac{\sqrt3}{2}i=e^{\,i\pi/3},\qquad 1+\omega^2=\tfrac12-\tfrac{\sqrt3}{2}i=e^{-i\pi/3}.

Both have modulus 11, so raising to the 99th power rotates the angle to ±3π\pm 3\pi:

(1+ω)9=e3πi=1,(1+ω2)9=e3πi=1.(1+\omega)^9=e^{\,3\pi i}=-1,\qquad (1+\omega^2)^9=e^{-3\pi i}=-1.

Therefore

S=13[512+(1)+(1)]=5103=170.S=\frac{1}{3}\bigl[512+(-1)+(-1)\bigr]=\frac{510}{3}=\boxed{170}.

(Check directly: 1+84+84+1=1701+84+84+1=170.)

Tip

Tips. (1) The complex factors always pair as conjugates, so their sum is real---write (1+ωj)n(1+\omega^j)^n in polar form RneinθR^n e^{in\theta} and add. (2) The general clean formula for m=3,r=0m=3,\,r=0 is k(n3k)=13(2n+2cosnπ3)\sum_k\binom{n}{3k}=\tfrac13\bigl(2^n+2\cos\tfrac{n\pi}{3}\bigr). (3) The same machine filters coefficients of any polynomial or power series, not just (1+x)n(1+x)^n---it is the standard tool for “count the objects whose size is r(modm)\equiv r\pmod m” problems.

The Generalized Binomial Series

Concept
Binomial coefficients with any upper index

Define, for any real (or complex) α\alpha and integer k0k\ge 0,

(αk)=α(α1)(α2)(αk+1)k!.\binom{\alpha}{k}=\frac{\alpha(\alpha-1)(\alpha-2)\cdots(\alpha-k+1)}{k!}.

Newton's generalized binomial theorem then extends the expansion to non-integer exponents: for x<1|x|<1,

(1+x)α=k=0(αk)xk.(1+x)^{\alpha}=\sum_{k=0}^{\infty}\binom{\alpha}{k}x^{k}.

When α=n\alpha=n is a nonnegative integer the numerator eventually hits the factor (αα)=0(\alpha-\alpha)=0, killing all terms past k=nk=n and recovering the ordinary finite Binomial Theorem. For other α\alpha the series is genuinely infinite.

Negative integer upper index (ties back to stars and bars). Setting α=n\alpha=-n and simplifying the falling product gives

(nk)=(1)k(n+k1k),\binom{-n}{k}=(-1)^k\binom{n+k-1}{k},

so that

1(1x)n=(1x)n=k=0(n+k1k)xk.\frac{1}{(1-x)^{n}}=(1-x)^{-n}=\sum_{k=0}^{\infty}\binom{n+k-1}{k}x^{k}.

The coefficient (n+k1k)\binom{n+k-1}{k} is exactly the stars-and-bars count of the ways to write kk as an ordered sum of nn nonnegative integers---so the negative binomial series is the generating function for distributing kk identical items into nn distinct boxes.

Example
Worked example (olympiad flavor): a square-root series

Show that the central binomial coefficients appear as the coefficients of (14x)1/2(1-4x)^{-1/2}; that is, prove [xk](14x)1/2=(2kk)\displaystyle [x^k](1-4x)^{-1/2}=\binom{2k}{k}.

Apply Newton's theorem with α=12\alpha=-\tfrac12 and the variable 4x-4x:

(14x)1/2=k=0(1/2k)(4)kxk.(1-4x)^{-1/2}=\sum_{k=0}^{\infty}\binom{-1/2}{k}(-4)^{k}x^{k}.

Now evaluate (1/2k)\binom{-1/2}{k}. The numerator is

(12)(32)(2k12)=(1)k135(2k1)2k=(1)k(2k)!2k2kk!,\Bigl(-\tfrac12\Bigr)\Bigl(-\tfrac32\Bigr)\cdots\Bigl(-\tfrac{2k-1}{2}\Bigr) =(-1)^k\,\frac{1\cdot 3\cdot 5\cdots(2k-1)}{2^{k}} =(-1)^k\,\frac{(2k)!}{2^{k}\,2^{k}\,k!},

using 13(2k1)=(2k)!2kk!1\cdot3\cdots(2k-1)=\dfrac{(2k)!}{2^{k}k!}. Hence

(1/2k)=(1)k(2k)!4kk!k!=(1)k14k(2kk).\binom{-1/2}{k}=(-1)^k\frac{(2k)!}{4^{k}\,k!\,k!}=(-1)^k\frac{1}{4^{k}}\binom{2k}{k}.

Multiplying by (4)k(-4)^k cancels both the sign and the 4k4^k:

[xk](14x)1/2=(1)k14k(2kk)(4)k=(2kk).[x^k](1-4x)^{-1/2}=(-1)^k\frac{1}{4^{k}}\binom{2k}{k}\cdot(-4)^k=\boxed{\binom{2k}{k}}.

This is the standard generating function k0(2kk)xk=(14x)1/2\sum_{k\ge0}\binom{2k}{k}x^k=(1-4x)^{-1/2}.

Tip

Tips. (1) The identity (nk)=(1)k(n+k1k)\binom{-n}{k}=(-1)^k\binom{n+k-1}{k} (“negating the upper index”) converts messy negative-index expressions into ordinary positive binomial coefficients. (2) Whenever a problem produces 1(1x)n\dfrac{1}{(1-x)^n}, read off (n+k1k)\binom{n+k-1}{k}---no separate stars-and-bars argument needed. (3) Fractional exponents (α=±12\alpha=\pm\tfrac12) generate central binomial and Catalan-number series, which recur throughout combinatorics.

Coefficient Extraction: The Unifying Method

Concept
Turning identities into products of series

Every summation identity in this unit is a shadow of a single equation between generating functions, read off by comparing one coefficient. The recipe: encode each side as a power series, multiply, and equate [xN][x^N]. Because multiplying series convolves their coefficients,

[xN]A(x)B(x)=k([xk]A)([xNk]B),[x^N]\,A(x)B(x)=\sum_{k}\bigl([x^k]A\bigr)\bigl([x^{N-k}]B\bigr),

a product of two known series manufactures a sum of products of coefficients---precisely the shape of Vandermonde, the subcommittee identity, and their kin. This “snake-oil” method turns the search for a closed form into the routine task of recognizing a product.

Example
Worked example (olympiad flavor): the subcommittee identity

Evaluate T=k=0n(nk)(km)\displaystyle T=\sum_{k=0}^{n}\binom{n}{k}\binom{k}{m} (a committee of size kk from nn people, with a distinguished sub-board of size mm).

Combinatorial read. Choosing a committee and then an mm-member sub-board is the same as choosing the mm-member board first ((nm)\binom{n}{m} ways) and then freely including or excluding each of the remaining nmn-m people (2nm2^{\,n-m} ways). So we expect T=(nm)2nmT=\binom{n}{m}2^{\,n-m}.

Coefficient-extraction proof. Write (km)=[ym](1+y)k\binom{k}{m}=[y^m](1+y)^k and sum a geometric-style series in xx using k(nk)((1+y)x)k=(1+(1+y)x)n\sum_k\binom{n}{k}\bigl((1+y)x\bigr)^k=(1+(1+y)x)^n. Setting x=1x=1,

k(nk)(1+y)k=(2+y)n,soT=[ym](2+y)n.\sum_{k}\binom{n}{k}(1+y)^k=(2+y)^n, \qquad\text{so}\qquad T=[y^m](2+y)^n.

By the ordinary Binomial Theorem (2+y)n=j(nj)2njyj(2+y)^n=\sum_{j}\binom{n}{j}2^{\,n-j}y^{j}, whose ymy^m coefficient is

T=(nm)2nm.T=\binom{n}{m}2^{\,n-m}.

Both stories agree, and the algebra needed nothing but “compare the coefficient of ymy^m.”

Tip

Master strategy. Faced with an unfamiliar binomial sum, encode it as [xN][x^N] of a product you recognize: use (1+x)a(1+x)b=(1+x)a+b(1+x)^a(1+x)^b=(1+x)^{a+b} for Vandermonde-type merges, 11x\dfrac{1}{1-x} to accumulate a running sum (this is Hockey Stick in disguise), and Newton's series from the previous section for negative or fractional exponents. Then the identity is proved the instant you name the coefficient. Combinatorial double-counting supplies the meaning; coefficient extraction supplies a mechanical proof---and together they make even AIME/olympiad-level binomial sums tractable.

Formulas, Proofs & Tips

Tip
The binomial theorem
(x+y)n=k=0n(nk)xnkyk(x+y)^{n}=\sum_{k=0}^{n}\binom{n}{k}x^{\,n-k}y^{k}

What it means. Expands any power of a binomial; (nk)\binom{n}{k} is row nn of Pascal's triangle.

Example. (x+1)3=x3+3x2+3x+1(x+1)^3=x^3+3x^2+3x+1, the coefficients 1,3,3,11,3,3,1 being (3k)\binom3k.

Why it works. Expanding (x+y)n(x+y)^n means choosing, from each of the nn factors, either xx or yy. A term with kk copies of yy arises once for every way of choosing which kk factors supply the yy — that count is (nk)\binom{n}{k}.

Tip. The term containing yky^k is (nk)xnkyk\binom{n}{k}x^{n-k}y^k, so you can grab a single coefficient without expanding everything.