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Handbook · Chapter 1

Algebra

Means, sequences and series, rates, systems, polynomials and Vieta, factorizations, floor functions and inequalities: every algebra formula in one place.

Book pages 6–32 · 89 entries

1.1 Mean, Median, Mode

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Definition 1.1.1 · Mean/Average

Mean=average of all terms=sum of all termsnumber of terms\text{Mean} = \text{average of all terms} = \frac{\text{sum of all terms}}{\text{number of terms}}

Learn it:Definition 18.0.1 · Mean/AverageSection 18.0a Mean, Median and Mode

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Definition 1.1.2 · Mode

Mode=most common term(s)\text{Mode} = \text{most common term(s)}

Learn it:Definition 18.0.3 · Mode

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Remark 1.1.3

There could be multiple modes. If the problem says "unique mode", it means that there is only one mode.

Learn it:Remark 18.0.4

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Definition 1.1.4 · Median

After arranging the numbers in increasing or decreasing order:

  • If the number of terms is odd, the median is the middle number.
  • If the number of terms is even, the median is the average of the middle two numbers.

Learn it:Definition 18.0.2 · Median

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Definition 1.1.5

The harmonic mean of the numbers a1,a2,a3,…,ana_1, a_2, a_3, \ldots, a_n is

11a1+1a2+⋯+1ann=n1a1+1a2+⋯+1an\frac{1}{\dfrac{\frac{1}{a_1} + \frac{1}{a_2} + \cdots + \frac{1}{a_n}}{n}} = \frac{n}{\frac{1}{a_1} + \frac{1}{a_2} + \cdots + \frac{1}{a_n}}

This means the harmonic mean is

nsum of the reciprocals of all ak\frac{n}{\text{sum of the reciprocals of all } a_k}

Learn it:Definition 18.0.6 · Harmonic MeanSection 18.0b Other Means

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1.2 Arithmetic Sequences

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Definition 1.2.1 · Arithmetic Sequence

An arithmetic sequence is a sequence of numbers with the same difference between consecutive terms.

1,4,7,10,13,…,401, 4, 7, 10, 13, \ldots, 40

is an arithmetic sequence because there is always a difference of 33 between consecutive terms.

Learn it:Definition 15.0.1 · Arithmetic SequenceSection 15.0 Arithmetic Sequences

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Remark 1.2.2

An arithmetic sequence can also have a negative common difference. For example, in the arithmetic sequence

40,37,34,…,4,140, 37, 34, \ldots, 4, 1

the common difference is −3-3.

Learn it:Remark 15.0.2

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Definition 1.2.3 · Arithmetic Sequence Notation

In general, the terms of an arithmetic sequence can be represented as

a1,a2,a3,a4,…,ana_1, a_2, a_3, a_4, \ldots, a_n

where

  • dd is the common difference between consecutive terms
  • nn is the number of terms

Learn it:Definition 15.0.3 · Arithmetic Sequence Notation

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Theorem 1.2.4 · nth term in an Arithmetic Sequence

an=a1+(n−1)da_n = a_1 + (n - 1)d

which means the nnth term of an arithmetic sequence is

first term+(n−1)(common difference).\text{first term} + (n - 1)(\text{common difference}).

We also have

an=am+(n−m)da_n = a_m + (n - m)d

which means

nth term=mth term+(n−m)(common difference).n\text{th term} = m\text{th term} + (n - m)(\text{common difference}).

Learn it:Theorem 15.0.4 · $n$th Term in an Arithmetic Sequence

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Theorem 1.2.5 · Number of Terms in an Arithmetic Sequence

n=an−a1d+1n = \frac{a_n - a_1}{d} + 1

Essentially,

Number of Terms=Last Term−First TermCommon Difference+1\text{Number of Terms} = \frac{\text{Last Term} - \text{First Term}}{\text{Common Difference}} + 1

Learn it:Theorem 15.0.5 · Number of Terms in an Arithmetic Sequence

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Theorem 1.2.6 · Average of Terms in an Arithmetic Sequence

Average of Terms=a1+an2\text{Average of Terms} = \frac{a_1 + a_n}{2}
Average of Terms=a1+a2+⋯+ann\text{Average of Terms} = \frac{a_1 + a_2 + \cdots + a_n}{n}

which essentially means

Average of Terms=First Term+Last Term2=Sum of all TermsNumber of Terms\text{Average of Terms} = \frac{\text{First Term} + \text{Last Term}}{2} = \frac{\text{Sum of all Terms}}{\text{Number of Terms}}
  • If the number of terms is even, the average is the average of the middle 22 terms.
  • If the number of terms is odd, the average is the middle term.

Learn it:Theorem 15.0.6 · Average of Terms in an Arithmetic Sequence

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Theorem 1.2.7 · Sum of all Terms in an Arithmetic Sequence

Sn=a1+an2×nS_n = \frac{a_1 + a_n}{2} \times n

which essentially means

Sum of All Terms=Average of Terms×Number of Terms.\text{Sum of All Terms} = \text{Average of Terms} \times \text{Number of Terms}.

We can also substitute an=a1+(n−1)da_n = a_1 + (n - 1)d to get

Sn=2a1+(n−1)d2×nS_n = \frac{2a_1 + (n - 1)d}{2} \times n

Learn it:Theorem 15.0.7 · Sum of All Terms in an Arithmetic Sequence

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1.3 Geometric Sequences

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Definition 1.3.2 · Geometric Sequence Notation

In general, the terms of a geometric sequence can be represented as

g1,g2,g3,g4,…,gng_1, g_2, g_3, g_4, \ldots, g_n

where

  • rr is the common ratio between consecutive terms
  • nn is the number of terms

Learn it:Definition 16.0.2 · Geometric Sequence Notation

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Remark 1.3.3

A geometric sequence can also have a negative common ratio. For example, the sequence 1,−2,4,−8,…,512,−10241, -2, 4, -8, \ldots, 512, -1024 has a common ratio of −2-2.

Learn it:Remark 16.0.3

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Theorem 1.3.4 · nth term in a Geometric Sequence

gn=g1⋅rn−1g_n = g_1 \cdot r^{n-1}

which means

nth term of a geometric sequence=first term×(common ratio)n−1.n\text{th term of a geometric sequence} = \text{first term} \times (\text{common ratio})^{n-1}.

A general form for calculating the nnth term is

gn=gm⋅rn−mg_n = g_m \cdot r^{n-m}

which means

nth term=mth term×(common ratio)n−m.n\text{th term} = m\text{th term} \times (\text{common ratio})^{n-m}.

Learn it:Theorem 16.0.4 · nth Term in a Geometric Sequence

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Theorem 1.3.5 · Number of Terms in a Finite Geometric Sequence

For r>0r > 0, r≠1r \ne 1,

n=log⁡r(gng1)+1n = \log_r\left(\frac{g_n}{g_1}\right) + 1

Essentially, the number of terms is 11 more than the number of times we need to multiply g1g_1 by rr to get gng_n.

Learn it:Section 16.0a Terms of a Geometric Sequence

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Theorem 1.3.6 · Sum of all Terms in a Finite Geometric Sequence

For r≠1r \ne 1,

Sn=g1⋅1−rn1−rS_n = g_1 \cdot \frac{1 - r^n}{1 - r}

which essentially means

Sum of All Terms=First Term×1−(common ratio)n1−common ratio.\text{Sum of All Terms} = \text{First Term} \times \frac{1 - (\text{common ratio})^n}{1 - \text{common ratio}}.

Learn it:Theorem 16.0.5 · Sum of All Terms in a Finite Geometric SequenceSection 16.0b Geometric Series

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Remark 1.3.8

The formula only works for ∣r∣<1|r| < 1 because if ∣r∣≥1|r| \ge 1 the sum diverges (essentially, it is infinite or never settles). We can only find the sum of a converging geometric sequence, whose sum approaches a constant value. Some examples:

1+12+14+18+⋯=11−12=21 + \frac12 + \frac14 + \frac18 + \cdots = \frac{1}{1 - \frac12} = 2
1+13+19+127+⋯=11−13=321 + \frac13 + \frac19 + \frac1{27} + \cdots = \frac{1}{1 - \frac13} = \frac32

Learn it:Remark 16.0.7

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1.4 Special Series

Theorem 1.4.2 · Sum of Odd Numbers Formula

1+3+5+⋯+(2n−1)=n21 + 3 + 5 + \cdots + (2n - 1) = n^2

In simple terms, the sum of the first nn odd numbers is n2n^2.

Learn it:Theorem 17.0.2 · Sum of odd numbers formula

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Theorem 1.4.3 · Sum of Even Numbers Formula

2+4+6+⋯+2n=n(n+1)2 + 4 + 6 + \cdots + 2n = n(n+1)

To think about it intuitively, just take 22 out of each term:

2(1+2+3+⋯+n)=2⋅n(n+1)2=n(n+1)2(1 + 2 + 3 + \cdots + n) = 2 \cdot \frac{n(n+1)}{2} = n(n+1)

In simple terms, the sum of the first nn even numbers is 2×2 \times the sum of the first nn numbers.

Learn it:Theorem 17.0.3 · Sum of even numbers formula

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Theorem 1.4.4 · Sum of Squares Formula

12+22+⋯+n2=n(n+1)(2n+1)61^2 + 2^2 + \cdots + n^2 = \frac{n(n+1)(2n+1)}{6}

Learn it:Theorem 17.0.4 · Sum of squares formula

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Theorem 1.4.5 · Sum of Cubes Formula

13+23+⋯+n3=(n(n+1)2)21^3 + 2^3 + \cdots + n^3 = \left(\frac{n(n+1)}{2}\right)^2

Learn it:Theorem 17.0.5 · Sum of cubes formula

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1.5 Telescoping

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Remark 1.5.2

Generally, whenever you have long expressions that seem to be hard or impossible to compute manually, telescoping is probably at play.

Learn it:Remark 17.1.2

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Concept 1.5.3 · Partial Fraction Decomposition

Partial fraction decomposition is a telescoping technique in which you split terms into multiple terms so that terms cancel. In general, to find the partial fraction decomposition of 1ab\frac{1}{ab} for any expressions aa and bb, we write the equation

xa+yb=1ab\frac{x}{a} + \frac{y}{b} = \frac{1}{ab}

and then solve for xx and yy. For example, the partial fraction decomposition of

1n(n+1)\frac{1}{n(n+1)}

(in this case a=na = n and b=n+1b = n + 1) is

1n−1n+1.\frac{1}{n} - \frac{1}{n+1}.

Using partial fraction decomposition, we can telescope and evaluate expressions easily.

Learn it:Section 17.1 Telescopingundefined 17.2.8

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1.6 Speed, Distance, and Time

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Theorem 1.6.2

Average Speed=Total DistanceTotal Time\text{Average Speed} = \frac{\text{Total Distance}}{\text{Total Time}}

Learn it:Theorem 20.0.2 · Average Speed

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Remark 1.6.3

A common mistake is to assume that average speed is the average of all the speeds (especially when the distance you travel at each of those speeds is the same). Remember, that's not true unless you travel at those speeds for the same amount of time!

Learn it:Remark 20.0.3 · The Average-Speed Trap

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1.7 Work, Rate, and Time

Theorem 1.7.1

Work=Rate×Time\text{Work} = \text{Rate} \times \text{Time}

Equivalently,

Rate=WorkTimeTime=WorkRate\text{Rate} = \frac{\text{Work}}{\text{Time}} \qquad \text{Time} = \frac{\text{Work}}{\text{Rate}}

Learn it:Theorem 19.1.1 · Work, Rate and TimeSection 19.1 Work and Rate

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1.8 System of Equations

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Concept 1.8.1 · System of Equations Word Problems

This is one of the most common topics on the AMC 10 especially. The trick to solving these problems is to assign variables to the unknowns in the problem and solve.

Learn it:Section 19.0 Setting Up Systems

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Concept 1.8.2 · Solving Systems of Equations

Once you've found the system of equations in your word problem (or the problem gives you a system of equations), consider one or more of the following methods for solving it.

  1. Substitution

  2. Elimination

  3. Diagonal Product Method (only for 2-variable equations)

  4. Adding/Subtracting Equations

  5. Be on the lookout for common factorization tricks (see Section 1.10)

  6. Constructing polynomials from your equations using Vieta's Formulas (see Section 1.9)

  7. Graphing your equations (we recommend graph paper)

  8. Using symmetry

  9. Creating a geometric setup using geometric formulas such as the

    • Law of Cosines
    • Heron's Formula
    • Sine area formula
    • Stewart's Theorem
    • Trig Identities

    (See the geometry chapter for these formulas.)

Learn it:Concept 12.5.1 · Algebraic Equations TechniquesSection 19.0 Setting Up Systems

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1.9 Polynomials

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Concept 1.9.1 · Discriminant

In the quadratic formula,

b2−4acb^2 - 4ac

(the part inside the square root) is the discriminant of the quadratic.

  1. If the discriminant b2−4acb^2 - 4ac is 00, then the quadratic has a double (repeated) root.
  2. If the discriminant b2−4acb^2 - 4ac is positive, the quadratic has 22 different real roots.
  3. If the discriminant b2−4acb^2 - 4ac is negative, the quadratic has no real roots.

Learn it:Concept 13.1.2 · DiscriminantSection 13.1a Quadratics: Formula, Discriminant and Vieta

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Remark 1.9.2

Also note that a quadratic (with integer coefficients) can only have integer solutions if the discriminant b2−4acb^2 - 4ac is a perfect square.

Learn it:Concept 13.1.2 · Discriminant

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Theorem 1.9.3 · Quadratic Formula

The solutions to the quadratic equation

ax2+bx+c=0ax^2 + bx + c = 0

are

x=−b±b2−4ac2ax = \frac{-b \pm \sqrt{b^2 - 4ac}}{2a}

Learn it:Theorem 13.1.1 · Quadratic Formula

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Theorem 1.9.4 · Vieta’s Formula For Quadratics

In a quadratic equation

ax2+bx+c=0ax^2 + bx + c = 0

the sum of its roots is

−ba-\frac{b}{a}

and the product of its roots is

ca.\frac{c}{a}.

Learn it:Theorem 13.1.3 · Vieta's Formula For Quadratics

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Theorem 1.9.5 · Vieta’s Formula For Higher Degree Polynomials

In a polynomial

anxn+an−1xn−1+⋯+a1x+a0=0a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0 = 0

with roots r1,r2,r3,…,rnr_1, r_2, r_3, \ldots, r_n, the following hold:

r1+r2+r3+⋯+rn=−an−1an(the sum of all products of 1 term)r_1 + r_2 + r_3 + \cdots + r_n = -\frac{a_{n-1}}{a_n} \quad \text{(the sum of all products of 1 term)}
r1r2+r1r3+⋯+rn−1rn=an−2an(the sum of all products of 2 terms)r_1r_2 + r_1r_3 + \cdots + r_{n-1}r_n = \frac{a_{n-2}}{a_n} \quad \text{(the sum of all products of 2 terms)}
r1r2r3+r1r2r4+⋯+rn−2rn−1rn=−an−3an(the sum of all products of 3 terms)r_1r_2r_3 + r_1r_2r_4 + \cdots + r_{n-2}r_{n-1}r_n = -\frac{a_{n-3}}{a_n} \quad \text{(the sum of all products of 3 terms)}
⋮\vdots
r1r2r3⋯rn=(−1)na0an(the product of all n terms)r_1r_2r_3\cdots r_n = (-1)^n\frac{a_0}{a_n} \quad \text{(the product of all } n \text{ terms)}

Note that the signs alternate: a sum of products of an odd number of roots gets a minus sign, and an even number gets a plus sign.

Learn it:Theorem 13.1.4 · Vieta's Formula For Higher Degree PolynomialsSection 13.1b Vieta for Higher-Degree Polynomials

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Theorem 1.9.6 · Rational Root theorem

In a polynomial

P(x)=anxn+an−1xn−1+⋯+a1x+a0P(x) = a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

where ana_n is nonzero and every aia_i is an integer, every rational root ±pq\pm\frac{p}{q} of the polynomial (in lowest terms) has

  • pp divides a0a_0
  • qq divides ana_n

Essentially,

  • the numerators of all fractional roots divide the constant term of the polynomial
  • the denominators of all fractional roots divide the coefficient of the largest-degree term.

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Corollary 1.9.7 · Integer Root theorem

In a polynomial

P(x)=anxn+an−1xn−1+⋯+a1x+a0P(x) = a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

where ana_n is nonzero and every aia_i is an integer, all integer roots of the polynomial must divide a0a_0, the constant term of the polynomial.

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Remark 1.9.8

This means that for polynomials with integer coefficients and a leading coefficient of 11 (monic polynomials), the only rational roots are integers.

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Corollary 1.9.10 · Factor Theorem

x−rx - r divides a polynomial P(x)P(x) if P(r)=0P(r) = 0.

This is a direct consequence of the Remainder Theorem.

Learn it:Corollary 14.1.6 · Factor Theorem

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Theorem 1.9.11 · Representation of Polynomial in terms of roots

A polynomial

P(x)=anxn+an−1xn−1+⋯+a1x+a0P(x) = a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

can be expressed in the form

an(x−r1)(x−r2)(x−r3)⋯(x−rn)a_n(x - r_1)(x - r_2)(x - r_3)\cdots(x - r_n)

where r1,r2,r3,…,rnr_1, r_2, r_3, \ldots, r_n are the nn roots of the polynomial.

Learn it:Theorem 14.1.1 · Representation of a Polynomial in Terms of Its RootsConcept 14.1.3 · Evaluating a Product of Differences

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Corollary 1.9.12 · Representation of Monic Polynomial in terms of roots

A polynomial

P(x)=xn+an−1xn−1+⋯+a1x+a0P(x) = x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

(with leading coefficient 11) can be expressed in the form

(x−r1)(x−r2)(x−r3)⋯(x−rn)(x - r_1)(x - r_2)(x - r_3)\cdots(x - r_n)

where r1,r2,r3,…,rnr_1, r_2, r_3, \ldots, r_n are the nn roots of the polynomial.

Learn it:Corollary 14.1.2 · Representation of a Monic Polynomial in Terms of Its Roots

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Theorem 1.9.15

If a+bca + b\sqrt{c} is a root of a polynomial with rational coefficients, where aa, bb, cc are rational and c\sqrt{c} is irrational, then a−bca - b\sqrt{c} is a root too.

Correction

The book does not require c\sqrt{c} to be irrational (or aa, bb rational). Without that the statement fails: 2=0+1⋅42 = 0 + 1\cdot\sqrt{4} is a root of x−2x - 2, but 0−1⋅4=−20 - 1\cdot\sqrt{4} = -2 is not.

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Concept 1.9.16 · Reciprocal Roots

If the polynomial

P(x)=anxn+an−1xn−1+⋯+a1x+a0P(x) = a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

has roots r1,r2,r3,…,rnr_1, r_2, r_3, \ldots, r_n, then

Q(x)=a0xn+a1xn−1+⋯+an−1x+anQ(x) = a_0 x^n + a_1 x^{n-1} + \cdots + a_{n-1}x + a_n

has roots

1r1,1r2,…,1rn.\frac{1}{r_1}, \frac{1}{r_2}, \ldots, \frac{1}{r_n}.

Essentially, when you flip the coefficients of a polynomial, its roots become the reciprocals of the original roots.

Learn it:Concept 14.3.1 · Reciprocal RootsSection 14.3 Polynomial Manipulations

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Concept 1.9.17 · Roots That Are More or Less

If the polynomial

P(x)=anxn+an−1xn−1+⋯+a1x+a0P(x) = a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

has roots r1,r2,r3,…,rnr_1, r_2, r_3, \ldots, r_n, then

Q(x)=an(x−k)n+an−1(x−k)n−1+⋯+a1(x−k)+a0Q(x) = a_n(x - k)^n + a_{n-1}(x - k)^{n-1} + \cdots + a_1(x - k) + a_0

has roots

r1+k,r2+k,r3+k,…,rn+k.r_1 + k, r_2 + k, r_3 + k, \ldots, r_n + k.

Learn it:Concept 14.3.2 · Roots That Are More or Less

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Remark 1.9.18

Remember: if the roots are kk more, then we subtract kk from each xx in our polynomial.

Learn it:Remark 14.3.3

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Remark 1.9.19

Polynomial manipulations are useful when evaluating complicated expressions in the roots. For example, to evaluate

1(r−3)3+1(s−3)3+1(t−3)3\frac{1}{(r - 3)^3} + \frac{1}{(s - 3)^3} + \frac{1}{(t - 3)^3}

for a polynomial with roots r,s,tr, s, t, rather than expanding it out and bashing with Vieta's Formulas, we can construct a new polynomial with roots

1(r−3)3,1(s−3)3,1(t−3)3\frac{1}{(r - 3)^3}, \frac{1}{(s - 3)^3}, \frac{1}{(t - 3)^3}

by the above methods and then simply find the sum of the roots of that polynomial.

Learn it:Remark 14.3.4

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Theorem 1.9.20 · Newton Sums

Let the polynomial

P(x)=anxn+an−1xn−1+⋯+a1x+a0P(x) = a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

have roots r1,r2,r3,…,rnr_1, r_2, r_3, \ldots, r_n, and let

Sk=r1k+r2k+⋯+rnk.S_k = r_1^k + r_2^k + \cdots + r_n^k.

Then the following hold:

anS1+an−1=0a_n S_1 + a_{n-1} = 0
anS2+an−1S1+2an−2=0a_n S_2 + a_{n-1}S_1 + 2a_{n-2} = 0
anS3+an−1S2+an−2S1+3an−3=0a_n S_3 + a_{n-1}S_2 + a_{n-2}S_1 + 3a_{n-3} = 0
⋮\vdots

Note that aj=0a_j = 0 whenever jj is negative, as that might show up in your expansion.

Essentially, this says:

  1. Start with SkS_k and multiply it by the leftmost coefficient ana_n.
  2. Then multiply Sk−1S_{k-1} by the next coefficient an−1a_{n-1}.
  3. Continue doing so and summing the products until either
    • you reach S0S_0, in which case instead of multiplying S0S_0 by that last coefficient you multiply it by kk, or
    • the coefficients run out, in which case you simply add the last term and stop.
  4. Set the sum equal to 00.
Correction

Step 2 of the book's recipe says to multiply Sn−1S_{n-1} by the next coefficient; it means Sk−1S_{k-1} (the power sums go down by one at each step, as in the equations above).

Learn it:Theorem 14.3.5 · Newton Sums

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Theorem 1.9.21

If

x+1x=ax + \frac{1}{x} = a

then

x2+1x2=a2−2x^2 + \frac{1}{x^2} = a^2 - 2
x3+1x3=a3−3ax^3 + \frac{1}{x^3} = a^3 - 3a
x4+1x4=(a2−2)2−2x^4 + \frac{1}{x^4} = \left(a^2 - 2\right)^2 - 2

Learn it:Theorem 12.1.3

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Definition 1.9.22 · Symmetric Polynomials

A polynomial

P(x)=anxn+an−1xn−1+⋯+a1x+a0P(x) = a_n x^n + a_{n-1}x^{n-1} + \cdots + a_1 x + a_0

is symmetric if

an=a0,an−1=a1,an−2=a2,an−3=a3,…a_n = a_0, \quad a_{n-1} = a_1, \quad a_{n-2} = a_2, \quad a_{n-3} = a_3, \quad \ldots

Basically, opposite coefficients are equal.

Learn it:Definition 14.2.1 · Symmetric PolynomialsSection 14.2 Symmetric Polynomials

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Concept 1.9.23 · Solving Symmetric Polynomials of Even Degree

To solve a symmetric polynomial P(x)=a0xn+a1xn−1+⋯+a1x+a0P(x) = a_0 x^n + a_1 x^{n-1} + \cdots + a_1 x + a_0 of even degree:

  • Divide by xn/2x^{n/2}.
  • Group the xkx^k and 1xk\frac{1}{x^k} terms together.
  • Make the substitution
y=x+1xy = x + \frac{1}{x}

and write all the terms in your expression that way.

  • Solve the reduced polynomial.

Learn it:Concept 14.2.2 · Solving Symmetric Polynomials of Even Degree

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Remark 1.9.24

Note that with the Newton Sum equations we can calculate each SkS_k iteratively, one after another, rather than having to bash with Vieta's Formulas.

Learn it:Remark 14.3.6

Book p. 24

1.10 Algebraic Manipulations

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Theorem 1.10.1 · Exponent Rules

For x≠0x \ne 0:

x−a=1xax^{-a} = \frac{1}{x^a}
xa×xb=xa+bx^a \times x^b = x^{a+b}
xa÷xb=xa−bx^a \div x^b = x^{a-b}
(xa)b=xab\left(x^a\right)^b = x^{ab}

Learn it:Theorem 12.0.1 · Exponent RulesSection 12.0 Exponent Rules

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Theorem 1.10.3 · Binomial Square Expansions

(x+y)2=x2+2xy+y2=(x−y)2+4xy(x + y)^2 = x^2 + 2xy + y^2 = (x - y)^2 + 4xy
(x−y)2=x2−2xy+y2=(x+y)2−4xy(x - y)^2 = x^2 - 2xy + y^2 = (x + y)^2 - 4xy
(x+y)2+(x−y)2=2(x2+y2)(x + y)^2 + (x - y)^2 = 2\left(x^2 + y^2\right)
(x+y)2−(x−y)2=4xy(x + y)^2 - (x - y)^2 = 4xy
(x+y+z)2=x2+y2+z2+2(xy+yz+xz)(x + y + z)^2 = x^2 + y^2 + z^2 + 2(xy + yz + xz)

Learn it:Theorem 12.1.1 · Binomial Square ExpansionsSection 12.1 Binomial Expansions

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Remark 1.10.5

You can generally apply this factorization when you have xyxy, xx, and yy terms. After applying the factorization, you can then find all possible values for each of the factors (remember negatives!).

Learn it:Remark 12.4.3Remark 25.3.2

Book p. 25

Theorem 1.10.7 · Sum of Cubes

x3+y3=(x+y)(x2−xy+y2)x^3 + y^3 = (x + y)\left(x^2 - xy + y^2\right)

Learn it:Theorem 12.3.2 · Sum of Cubes

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Theorem 1.10.8 · Binomial Cube Expansions

(x+y)3=x3+3xy(x+y)+y3(x + y)^3 = x^3 + 3xy(x + y) + y^3
(x+y)3=x3+3x2y+3xy2+y3(x + y)^3 = x^3 + 3x^2y + 3xy^2 + y^3
(x−y)3=x3−3xy(x−y)−y3(x - y)^3 = x^3 - 3xy(x - y) - y^3
(x−y)3=x3−3x2y+3xy2−y3(x - y)^3 = x^3 - 3x^2y + 3xy^2 - y^3
x3+y3+z3−3xyz=(x+y+z)(x2+y2+z2−xy−xz−yz)x^3 + y^3 + z^3 - 3xyz = (x + y + z)\left(x^2 + y^2 + z^2 - xy - xz - yz\right)

Learn it:Theorem 12.1.2 · Binomial Cube Expansions

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Theorem 1.10.9 · nth power Factorizations

Sum of odd powers:

x2n+1+y2n+1=(x+y)(x2n−x2n−1y+x2n−2y2−⋯−xy2n−1+y2n)x^{2n+1} + y^{2n+1} = (x + y)\left(x^{2n} - x^{2n-1}y + x^{2n-2}y^2 - \cdots - xy^{2n-1} + y^{2n}\right)

The signs in the second factor alternate between positive and negative.

Difference of powers:

xn−yn=(x−y)(xn−1+xn−2y+xn−3y2+⋯+xyn−2+yn−1)x^n - y^n = (x - y)\left(x^{n-1} + x^{n-2}y + x^{n-3}y^2 + \cdots + xy^{n-2} + y^{n-1}\right)

The signs in the second factor are all positive.

Learn it:Theorem 12.4.1 · nth Power FactorizationsTheorem 25.4.1 · nth Power FactorizationsSection 12.4 Higher Power Factorizations

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Remark 1.10.11

Be on the lookout for 4th powers to apply Sophie Germain's Identity!

Learn it:Remark 25.5.2

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Concept 1.10.12 · Algebraic Manipulation Techniques

Here are some ideas for algebraic manipulation:

  1. Group similar terms together.
  2. Be on the lookout for factorizations.
  3. Take advantage of symmetry; you can use it to construct polynomials.
  4. Make smart substitutions that simplify your expression. For example, if the term
49−x2\sqrt{49 - x^2}

appears multiple times in your expression, just let

y=49−x2y = \sqrt{49 - x^2}

to simplify it.

Learn it:Concept 12.5.1 · Algebraic Equations TechniquesSection 12.5 Algebraic Equations

Book p. 27

1.11 Floor and Ceiling Functions

Definition 1.11.1 · Floor, Ceiling, and Fractional Part Functions

⌊x⌋=greatest integer less than or equal to x\lfloor x \rfloor = \text{greatest integer less than or equal to } x
⌈x⌉=smallest integer greater than or equal to x\lceil x \rceil = \text{smallest integer greater than or equal to } x
{x}=fractional part of x (the value after the decimal point)\{x\} = \text{fractional part of } x \text{ (the value after the decimal point)}

Learn it:Definition 39.0.1 · Floor, Ceiling, and Fractional Part FunctionsSection 39.0 Floor, Ceiling and Fractional Part

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Remark 1.11.2

Common Floor and Ceiling Problem Techniques. Most floor and ceiling problems can be solved using these techniques.

  1. Make the substitution x=⌊x⌋+{x}x = \lfloor x \rfloor + \{x\}.
  2. Use the floor or ceiling function to find an inequality. For example, if you know that y=⌊x⌋y = \lfloor x \rfloor, then y≤x<y+1y \le x < y + 1.
  3. Graph your equations and look for intersection points (we recommend using graph paper).

Learn it:Concept 39.0.2 · Common Floor and Ceiling Problem Techniques

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1.12 Inequalities

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Corollary 1.12.2 · Completing the Square

In a quadratic Q(x)=ax2+bx+cQ(x) = ax^2 + bx + c,

  • If a>0a > 0, then the minimum value of Q(x)Q(x) is c−b24ac - \frac{b^2}{4a} and occurs when x=−b2ax = -\frac{b}{2a}.
  • If a<0a < 0, then the maximum value of Q(x)Q(x) is c−b24ac - \frac{b^2}{4a} and occurs when x=−b2ax = -\frac{b}{2a}.

Learn it:Corollary 40.1.2 · Completing the Square

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Remark 1.12.3

Simple, yet powerful. This is the core of all inequalities and how more advanced inequalities are derived.

The rest of the inequalities are optional for the AMC 10 but are still good to know.

Learn it:Remark 40.1.3

Book p. 29

Theorem 1.12.4 · AM-GM Inequality For 2 variables

For non-negative reals aa and bb,

a+b2≥ab\frac{a+b}{2} \ge \sqrt{ab}

Basically, this means the average of 22 non-negative numbers (arithmetic mean) is always at least as big as the square root of the product of the 22 numbers (the geometric mean).

Equality occurs when a=ba = b.

Learn it:Theorem 40.2.1 · AM-GM Inequality For 2 variablesSection 40.2 AM-GM

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Corollary 1.12.5

For x>0x > 0, the minimum value of x+1xx + \frac{1}{x} is 22 and occurs when x=1x = 1.

Correction

The book states this without a condition on xx. It needs x>0x > 0: for x=−1x = -1, x+1x=−2<2x + \frac1x = -2 < 2.

Learn it:Corollary 40.2.2

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Corollary 1.12.6

For positive aa and bb:

  • The minimum value of a+ba + b (if abab remains constant) occurs when a=ba = b.
  • The maximum value of abab (if a+ba + b remains constant) occurs when a=ba = b.
Correction

The book gives no domain. The first bullet needs a,b>0a, b > 0: with ab=1ab = 1 fixed, a=b=−1a = b = -1 gives a+b=−2a + b = -2, and a=−2a = -2, b=−12b = -\frac12 gives an even smaller sum −52-\frac52.

Learn it:Corollary 40.2.2

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Theorem 1.12.7 · AM-GM Inequality For More Variables

For non-negative reals a1,a2,…,ana_1, a_2, \ldots, a_n,

a1+a2+⋯+ann≥a1⋅a2⋅a3⋯ann\frac{a_1 + a_2 + \cdots + a_n}{n} \ge \sqrt[n]{a_1 \cdot a_2 \cdot a_3 \cdots a_n}

Equality occurs when a1=a2=⋯=ana_1 = a_2 = \cdots = a_n (all the variables are equal).

Another way to say this is

Average of n numbers≥product of all n numbersn\text{Average of } n \text{ numbers} \ge \sqrt[n]{\text{product of all } n \text{ numbers}}
Correction

The book's restatement in words has an equals sign, “Average of nn numbers == product of all n numbersn\sqrt[n]{\text{product of all } n \text{ numbers}}”; it should be ≥\ge (equality only when all the numbers are equal).

Learn it:Theorem 40.2.3 · AM-GM Inequality For More Variables

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Remark 1.12.8

This means in general,

min⁡(a1+a2+a3+⋯+an)=n⋅a1⋅a2⋅a3⋯ann\min(a_1 + a_2 + a_3 + \cdots + a_n) = n \cdot \sqrt[n]{a_1 \cdot a_2 \cdot a_3 \cdots a_n}
max⁡(a1⋅a2⋅a3⋯an)=(a1+a2+⋯+ann)n\max(a_1 \cdot a_2 \cdot a_3 \cdots a_n) = \left(\frac{a_1 + a_2 + \cdots + a_n}{n}\right)^n

Essentially,

min⁡(sum of all numbers)=n⋅product of all numbersn\min(\text{sum of all numbers}) = n \cdot \sqrt[n]{\text{product of all numbers}}
max⁡(product of all numbers)=(average of all numbers)n\max(\text{product of all numbers}) = (\text{average of all numbers})^n

Learn it:Remark 40.2.4

Book p. 30

Remark 1.12.9

Generally, we use AM-GM to maximize products or minimize sums.

Learn it:Remark 40.2.5

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Theorem 1.12.10 · Weighted AM-GM Inequality

For non-negative reals aia_i, cic_i,

c1a1+c2a2+⋯+cnanc1+c2+⋯+cn≥a1c1⋅a2c2⋅a3c3⋯ancnc1+c2+⋯+cn\frac{c_1 a_1 + c_2 a_2 + \cdots + c_n a_n}{c_1 + c_2 + \cdots + c_n} \ge \sqrt[c_1 + c_2 + \cdots + c_n]{a_1^{c_1} \cdot a_2^{c_2} \cdot a_3^{c_3} \cdots a_n^{c_n}}

Learn it:Theorem 40.2.6 · Weighted AM-GM Inequality

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Remark 1.12.11

Weighted AM-GM is very similar to AM-GM. One way to visualize weighted AM-GM is that there are ckc_k terms which are all equal to aka_k. So instead of writing ak+ak+⋯+aka_k + a_k + \cdots + a_k (ckc_k times) in our sum we simply write ak⋅cka_k \cdot c_k, and instead of writing ak⋅ak⋯aka_k \cdot a_k \cdots a_k (ckc_k times) in our product we simply write akcka_k^{c_k}.

Learn it:Remark 40.2.7

Book p. 30

Remark 1.12.12

We use weighted AM-GM when we are trying to make the sum of all terms a constant by multiplying weights to all (or some) of the terms. Remember to divide by the weights you multiplied at the end.

Learn it:Remark 40.2.8

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Theorem 1.12.13 · Cauchy Schwarz

For reals aia_i and bib_i,

(a1b1+a2b2+⋯+anbn)2≤(a12+a22+⋯+an2)(b12+b22+⋯+bn2)(a_1 b_1 + a_2 b_2 + \cdots + a_n b_n)^2 \le \left(a_1^2 + a_2^2 + \cdots + a_n^2\right)\left(b_1^2 + b_2^2 + \cdots + b_n^2\right)

This means

(the sum of the products of all ak and bk)2≤the product of the sums of squares of all ak and all bk.(\text{the sum of the products of all } a_k \text{ and } b_k)^2 \le \text{the product of the sums of squares of all } a_k \text{ and all } b_k.

Equality holds when the ratio aibi\frac{a_i}{b_i} is the same for all ii.

Learn it:Theorem 40.3.1 · Cauchy-SchwarzSection 40.3 Cauchy-Schwarz

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Remark 1.12.14

If you ever forget which way the ≤\le sign faces, just try a small example like a1=1a_1 = 1, a2=2a_2 = 2, b1=3b_1 = 3, and b2=4b_2 = 4.

Learn it:Remark 40.3.2

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Remark 1.12.15

You generally want to apply Cauchy-Schwarz when you are dealing with sums of squares.

Learn it:Remark 40.3.3

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Corollary 1.12.16 · Titu’s Lemma

For reals aia_i and positive reals bib_i,

a12b1+a22b2+⋯+an2bn≥(a1+a2+⋯+an)2b1+b2+b3+⋯+bn\frac{a_1^2}{b_1} + \frac{a_2^2}{b_2} + \cdots + \frac{a_n^2}{b_n} \ge \frac{(a_1 + a_2 + \cdots + a_n)^2}{b_1 + b_2 + b_3 + \cdots + b_n}

Alternately (for non-negative aia_i),

a1b1+a2b2+⋯+anbn≥(a1+a2+⋯+an)2b1+b2+b3+⋯+bn\frac{a_1}{b_1} + \frac{a_2}{b_2} + \cdots + \frac{a_n}{b_n} \ge \frac{\left(\sqrt{a_1} + \sqrt{a_2} + \cdots + \sqrt{a_n}\right)^2}{b_1 + b_2 + b_3 + \cdots + b_n}

Note that this is a direct consequence of Cauchy-Schwarz.

Correction

The book says “for reals aia_i and bib_i”. The bib_i must be positive (and the aia_i non-negative in the square-root form): with a=(1,1)a = (1, 1) and b=(1,−12)b = (1, -\frac12) the left side is −1-1 but the right side is 88.

Learn it:Corollary 40.3.4 · Titu's Lemma

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Concept 1.12.17 · Techniques For Optimization Problems

Steps to find the maximum/minimum of expressions:

  1. Use one (or possibly more) of these inequalities to find a simple expression that is greater than or equal to the given expression (for a maximization) or less than or equal to it (for a minimization):
    1. Trivial Inequality
    2. AM-GM
    3. Weighted AM-GM (AM-GM, weighted and unweighted, is useful for maximizing products and minimizing sums)
    4. Cauchy-Schwarz (useful when dealing with sums of squares)
  2. Verify that the equality case of your inequality can hold under your problem's conditions.
  3. Simplify your equality case and solve for the answer.

Learn it:Concept 40.3.5 · Techniques For Optimization Problems

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