AP Course

AP Calculus AB/BC

Study the complete College Board sequence for AP Calculus AB and BC, from limits through infinite series.

Choose an official unit and topic to open its lecture, concept check, or focused practice.

Lessons
1.1 Introducing Calculus: Can Change Occur at an Instant?1.2 Defining Limits and Using Limit Notation1.3 Estimating Limit Values from Graphs1.4 Estimating Limit Values from Tables1.5 Determining Limits Using Algebraic Properties of Limits1.6 Determining Limits Using Algebraic Manipulation1.7 Selecting Procedures for Determining Limits1.8 Determining Limits Using the Squeeze Theorem1.9 Connecting Multiple Representations of Limits1.10 Exploring Types of Discontinuities1.11 Defining Continuity at a Point1.12 Confirming Continuity over an Interval1.13 Removing Discontinuities1.14 Connecting Infinite Limits and Vertical Asymptotes1.15 Connecting Limits at Infinity and Horizontal Asymptotes1.16 Working with the Intermediate Value Theorem (IVT)2.1 Defining Average and Instantaneous Rates of Change at a Point2.2 Defining the Derivative of a Function and Using Derivative Notation2.3 Estimating Derivatives of a Function at a Point2.4 Connecting Differentiability and Continuity: Determining When Derivatives Do and Do Not Exist2.5 Applying the Power Rule2.6 Derivative Rules: Constant, Sum, Difference, and Constant Multiple2.7 Derivatives of cos x, sin x, e^x, and ln x2.8 The Product Rule2.9 The Quotient Rule2.10 Finding the Derivatives of Tangent, Cotangent, Secant, and/or Cosecant Functions3.1 The Chain Rule3.2 Implicit Differentiation3.3 Differentiating Inverse Functions3.4 Differentiating Inverse Trigonometric Functions3.5 Selecting Procedures for Calculating Derivatives3.6 Calculating Higher-Order Derivatives4.1 Interpreting the Meaning of the Derivative in Context4.2 Straight-Line Motion: Connecting Position, Velocity, and Acceleration4.3 Rates of Change in Applied Contexts Other Than Motion4.4 Introduction to Related Rates4.5 Solving Related Rates Problems4.6 Approximating Values of a Function Using Local Linearity and Linearization4.7 Using L’Hospital’s Rule for Determining Limits of Indeterminate Forms5.1 Using the Mean Value Theorem5.2 Extreme Value Theorem, Global Versus Local Extrema, and Critical Points5.3 Determining Intervals on Which a Function Is Increasing or Decreasing5.4 Using the First Derivative Test to Determine Relative (Local) Extrema5.5 Using the Candidates Test to Determine Absolute (Global) Extrema5.6 Determining Concavity of Functions over Their Domains5.7 Using the Second Derivative Test to Determine Extrema5.8 Sketching Graphs of Functions and Their Derivatives5.9 Connecting a Function, Its First Derivative, and Its Second Derivative5.10 Introduction to Optimization Problems5.11 Solving Optimization Problems5.12 Exploring Behaviors of Implicit Relations6.1 Exploring Accumulations of Change6.2 Approximating Areas with Riemann Sums6.3 Riemann Sums, Summation Notation, and Definite Integral Notation6.4 The Fundamental Theorem of Calculus and Accumulation Functions6.5 Interpreting the Behavior of Accumulation Functions Involving Area6.6 Applying Properties of Definite Integrals6.7 The Fundamental Theorem of Calculus and Definite Integrals6.8 Finding Antiderivatives and Indefinite Integrals: Basic Rules and Notation6.9 Integrating Using Substitution6.10 Integrating Functions Using Long Division and Completing the Square6.11 Integrating Using Integration by Parts6.12 Using Linear Partial Fractions6.13 Evaluating Improper Integrals6.14 Selecting Techniques for Antidifferentiation7.1 Modeling Situations with Differential Equations7.2 Verifying Solutions for Differential Equations7.3 Sketching Slope Fields7.4 Reasoning Using Slope Fields7.5 Approximating Solutions Using Euler’s Method7.6 Finding General Solutions Using Separation of Variables7.7 Finding Particular Solutions Using Initial Conditions and Separation of Variables7.8 Exponential Models with Differential Equations7.9 Logistic Models with Differential Equations8.1 Finding the Average Value of a Function on an Interval8.2 Connecting Position, Velocity, and Acceleration of Functions Using Integrals8.3 Using Accumulation Functions and Definite Integrals in Applied Contexts8.4 Finding the Area Between Curves Expressed as Functions of x8.5 Finding the Area Between Curves Expressed as Functions of y8.6 Finding the Area Between Curves That Intersect at More Than Two Points8.7 Volumes with Cross Sections: Squares and Rectangles8.8 Volumes with Cross Sections: Triangles and Semicircles8.9 Volume with Disc Method: Revolving Around the x- or y-Axis8.10 Volume with Disc Method: Revolving Around Other Axes8.11 Volume with Washer Method: Revolving Around the x- or y-Axis8.12 Volume with Washer Method: Revolving Around Other Axes8.13 The Arc Length of a Smooth, Planar Curve and Distance Traveled9.1 Defining and Differentiating Parametric Equations9.2 Second Derivatives of Parametric Equations9.3 Finding Arc Lengths of Curves Given by Parametric Equations9.4 Defining and Differentiating Vector-Valued Functions9.5 Integrating Vector-Valued Functions9.6 Solving Motion Problems Using Parametric and Vector-Valued Functions9.7 Defining Polar Coordinates and Differentiating in Polar Form9.8 Find the Area of a Polar Region or the Area Bounded by a Single Polar Curve9.9 Finding the Area of the Region Bounded by Two Polar Curves10.1 Defining Convergent and Divergent Infinite Series10.2 Working with Geometric Series10.3 The nth Term Test for Divergence10.4 Integral Test for Convergence10.5 Harmonic Series and p-Series10.6 Comparison Tests for Convergence10.7 Alternating Series Test for Convergence10.8 Ratio Test for Convergence10.9 Determining Absolute or Conditional Convergence10.10 Alternating Series Error Bound10.11 Finding Taylor Polynomial Approximations of Functions10.12 Lagrange Error Bound10.13 Radius and Interval of Convergence of Power Series10.14 Finding Taylor or Maclaurin Series for a Function10.15 Representing Functions as Power Series
Quizzes
Practice Problems AP formula notes, graph references, and practice sets will be added here.

AP Calculus AB/BC · Unit 10 · Topic 10.11 · BC Only

Finding Taylor Polynomial Approximations of Functions

Construct a local polynomial whose derivatives match a function at a chosen center, then use it to approximate nearby values.

1. Topic Focus

Determine series convergence, estimate error, construct Taylor approximations, and represent functions with power series on valid intervals.

This topic: Construct a local polynomial whose derivatives match a function at a chosen center, then use it to approximate nearby values.

2. Key Relationship

\(P_n(x)=\sum_{k=0}^n\frac{f^{(k)}(a)}{k!}(x-a)^k\)

Read every symbol with its domain, direction, units, and hypotheses before applying the relationship.

3. Visual Connection

center aerror
Taylor approximationThe polynomial matches derivatives at the center; the remainder bound controls separation farther away.

4. Worked Example

Keep the center shift, factorial denominators, and distinction between an approximation and an exact equality visible.

Write the governing relationship first, carry out the algebra cleanly, and finish with a sentence that answers the mathematical question.

5. Concept Development

BC-only topic. A Taylor polynomial replaces a sufficiently differentiable function by a polynomial that has the same local value, slope, concavity, and higher-derivative behavior at a chosen center.

The degree-n Taylor polynomial

For a function \(f\) centered at \(x=a\),

\(\boxed{P_n(x)=f(a)+f'(a)(x-a)+\frac{f''(a)}{2!}(x-a)^2+\cdots+\frac{f^{(n)}(a)}{n!}(x-a)^n.}\)

In sigma notation,

\(P_n(x)=\sum_{k=0}^{n}\frac{f^{(k)}(a)}{k!}(x-a)^k.\)

Why the coefficients contain factorials

If \(P_n(x)=c_0+c_1(x-a)+\cdots+c_n(x-a)^n\), then evaluating its \(k\)th derivative at the center removes every other power and gives

\(P_n^{(k)}(a)=k!c_k.\)

To force \(P_n^{(k)}(a)=f^{(k)}(a)\), the coefficient must be \(c_k=f^{(k)}(a)/k!\).

Derivative-matching property

\(P_n(a)=f(a),\quad P_n'(a)=f'(a),\quad\ldots,\quad P_n^{(n)}(a)=f^{(n)}(a).\)

The degree-\(1\) Taylor polynomial is the familiar tangent-line approximation. Degree \(2\) also matches concavity, and each higher degree captures one more derivative at the center.

Taylor versus Maclaurin

  • Taylor polynomial: centered at any specified \(a\), so powers are \((x-a)^k\).
  • Maclaurin polynomial: the special case \(a=0\), so powers are \(x^k\).

Maclaurin is not a different formula; it is a Taylor polynomial centered at zero.

A construction workflow

  1. Identify the center \(a\) and requested degree \(n\).
  2. Find \(f(a),f'(a),\ldots,f^{(n)}(a)\).
  3. Place each value over its matching factorial.
  4. Use powers of \(x-a\), not powers of \(x\), unless \(a=0\).
  5. Retain zero coefficients when they clarify the requested degree or derivative pattern.
  6. Simplify only after the structure is correct.

Using the polynomial to approximate a value

For an input \(x=a+h\) near the center, substitute into the polynomial:

\(f(a+h)\approx P_n(a+h)=\sum_{k=0}^{n}\frac{f^{(k)}(a)}{k!}h^k.\)

The approximation is usually better when \(|h|\) is small and when an appropriate higher degree is used. Topic 10.12 supplies a guaranteed Lagrange error bound.

Approximation is not automatic equality

Write \(f(x)\approx P_n(x)\) unless \(f\) itself is a polynomial of degree at most \(n\) or an exact equality has been established. Matching finitely many derivatives at one point does not make two functions identical everywhere.

Degree versus number of nonzero terms

A degree-\(n\) Taylor polynomial includes powers through \((x-a)^n\), but some coefficients may be zero. For example, the degree-\(5\) Maclaurin polynomial for \(\sin x\) has only three nonzero terms.

Reading derivative data from a table

If a table supplies \(f^{(k)}(a)\), insert those values directly. Do not differentiate the table entries or treat \(f^{(k)}(a)\) as the coefficient before dividing by \(k!\).

Recovering derivatives from a polynomial

If a Taylor polynomial centered at \(a\) contains \(c_k(x-a)^k\), then

\(f^{(k)}(a)=k!c_k.\)

A missing power has coefficient zero, so the corresponding derivative at the center is zero.

Finding derivatives from a differential equation

When \(f\) is defined by an initial-value problem, use the equation to find \(f'(a)\), differentiate the equation to obtain \(f''(a)\), and continue recursively. Substitute the initial condition after each derivative formula is valid.

Choosing a useful center

A center close to the target input keeps powers of \(h=x-a\) small. Centers where function and derivative values are simple, such as \(0\), \(1\), or a special trigonometric angle, also reduce arithmetic.

AP-style checklist

  1. State the center and degree.
  2. Show the needed derivative values at the center.
  3. Write the polynomial explicitly with factorial denominators.
  4. Use the correct shifted power in every term.
  5. For a numerical approximation, substitute the requested input into the displayed polynomial.
  6. Use approximation notation and round only at the end.

6. Detailed Worked Example and Error Check

Example 1: Exponential Maclaurin polynomial

Every derivative of \(e^x\) equals \(e^x\), so every derivative value at \(0\) is \(1\). Thus

\(P_4(x)=1+x+\frac{x^2}{2!}+\frac{x^3}{3!}+\frac{x^4}{4!}.\)

For example, \(e^{0.2}\approx P_4(0.2)\approx1.2214\).

Example 2: Sine and zero coefficients

The derivatives of \(\sin x\) cycle through \(\sin x,\cos x,-\sin x,-\cos x\). At \(0\), the values cycle \(0,1,0,-1\). The degree-\(5\) polynomial is

\(P_5(x)=x-\frac{x^3}{3!}+\frac{x^5}{5!}.\)

Although only three terms are nonzero, the highest power is \(5\).

Example 3: Cosine Maclaurin polynomial

Using the cosine derivative cycle,

\(P_6(x)=1-\frac{x^2}{2!}+\frac{x^4}{4!}-\frac{x^6}{6!}.\)

The odd-power coefficients vanish because every odd derivative of \(\cos x\) is zero at the origin.

Example 4: Logarithm centered at 1

For \(f(x)=\ln x\), the first derivative values at \(1\) are \(1,-1,2\). Hence

\(P_3(x)=(x-1)-\frac{(x-1)^2}{2}+\frac{(x-1)^3}{3}.\)

At \(x=1.2\), \(\ln(1.2)\approx0.2-0.02+0.008/3\approx0.182667\).

Example 5: Square root centered at 4

For \(f(x)=\sqrt x\),

\(f(4)=2,\qquad f'(4)=\frac14,\qquad f''(4)=-\frac1{32}.\)

Therefore

\(P_2(x)=2+\frac{x-4}{4}-\frac{(x-4)^2}{64}.\)

This gives \(\sqrt{4.1}\approx P_2(4.1)=2.02484375\).

Example 6: Construct from a derivative table

Suppose \(f(2)=3\), \(f'(2)=-1\), \(f''(2)=4\), and \(f'''(2)=6\). Then

\(P_3(x)=3-(x-2)+2(x-2)^2+(x-2)^3.\)

Thus \(f(2.1)\approx3-0.1+2(0.1)^2+(0.1)^3=2.921\).

Example 7: Recover derivative values

Suppose the fourth-degree Taylor polynomial centered at \(-1\) is

\(P_4(x)=2-3(x+1)+5(x+1)^3.\)

Then \(f(-1)=2\), \(f'(-1)=-3\), \(f''(-1)=0\), \(f'''(-1)=3!(5)=30\), and \(f^{(4)}(-1)=0\).

Example 8: Initial-value problem

Let \(y'=xy\) and \(y(0)=2\). Successive differentiation gives

\(y'(0)=0,\qquad y''(0)=2,\qquad y'''(0)=0,\qquad y^{(4)}(0)=6.\)

Therefore the degree-\(4\) Maclaurin polynomial is

\(P_4(x)=2+x^2+\frac{x^4}{4}.\)

Example 9: The tangent line is P1

If \(f(3)=7\) and \(f'(3)=-2\), then

\(P_1(x)=7-2(x-3).\)

This is exactly the linearization of \(f\) at \(x=3\).

Example 10: Exactness for a polynomial

If \(f(x)=x^3-2x+4\), its degree-\(3\) Taylor polynomial about any center equals \(f(x)\) after expansion. All derivatives above the third are zero, so no remainder remains.

Common errors

  • Forgetting the factorial in a coefficient.
  • Using \(x^k\) instead of \((x-a)^k\) at a nonzero center.
  • Substituting the target input as the center.
  • Confusing degree \(n\) with \(n\) nonzero terms.
  • Writing \(f(x)=P_n(x)\) when only an approximation is justified.
  • Using \(f^{(k)}(a)\) directly as the coefficient instead of dividing by \(k!\).
  • Dropping a zero coefficient and then misidentifying the requested degree.
  • Reading \(c_k\) as \(f^{(k)}(a)\) when extracting derivatives.
  • Rounding derivative values before constructing the polynomial.
  • Using an error-bound formula from Topic 10.12 without checking its hypotheses.
  • Giving only a numerical approximation when the polynomial itself is requested.

7. AP Reasoning Routine

Check the nth-term condition first, match the series structure to a justified test, state convergence type, and test power-series endpoints separately.

  • Identify the representation and requested quantity.
  • State the rule or theorem and verify its conditions.
  • Keep exact values until the final requested approximation.
  • Interpret sign, units, interval, and context.
AP Checkpoint

Construct the requested Taylor polynomial or use it as directed.
(a) Find the degree-\(3\) Maclaurin polynomial for \(e^x\).
(b) Find the degree-\(4\) Maclaurin polynomial for \(\cos x\).
(c) Find the degree-\(4\) Taylor polynomial for \(\ln x\) centered at \(1\).
(d) Find the degree-\(2\) Taylor polynomial for \(\sqrt x\) centered at \(9\).
(e) Given \(f(-2)=5\), \(f'(-2)=0\), \(f''(-2)=-6\), and \(f'''(-2)=12\), find \(P_3(x)\).
(f) If \(P_4(x)=1+2(x-3)-4(x-3)^2+(x-3)^4\), find \(f(3)\), \(f'(3)\), \(f''(3)\), \(f'''(3)\), and \(f^{(4)}(3)\).
(g) Use the degree-\(3\) Maclaurin polynomial for \(e^x\) to approximate \(e^{0.1}\).
(h) Use the degree-\(3\) Taylor polynomial for \(\ln x\) centered at \(1\) to approximate \(\ln(0.9)\).
(i) If \(y'=y\) and \(y(0)=3\), find the degree-\(3\) Maclaurin polynomial for \(y\).
(j) Explain why \(x-x^3/6+x^5/120\) is a degree-\(5\) polynomial even though it has only three nonzero terms.
(k) Two functions have equal derivatives through order \(4\) at \(x=a\). What can be concluded about their fourth-degree Taylor polynomials centered at \(a\)?
(l) Given \(f(1)=2\), \(f'(1)=3\), and \(f''(1)=-4\), write \(P_2(x)\) and use it to approximate \(f(1.05)\).

Check the solution

(a) \(P_3(x)=1+x+x^2/2+x^3/6\).
(b) \(P_4(x)=1-x^2/2+x^4/24\).
(c) \(P_4(x)=(x-1)-(x-1)^2/2+(x-1)^3/3-(x-1)^4/4\).
(d) Since \(f(9)=3\), \(f'(9)=1/6\), and \(f''(9)=-1/108\), \(P_2(x)=3+(x-9)/6-(x-9)^2/216\).
(e) \(P_3(x)=5-3(x+2)^2+2(x+2)^3\).
(f) \(f(3)=1\), \(f'(3)=2\), \(f''(3)=2!(-4)=-8\), \(f'''(3)=0\), and \(f^{(4)}(3)=4!(1)=24\).
(g) \(e^{0.1}\approx1+0.1+0.1^2/2+0.1^3/6\approx1.105167\).
(h) With \(h=-0.1\), \(\ln(0.9)\approx h-h^2/2+h^3/3=-0.105333\).
(i) Since every derivative equals \(y\), each derivative value at \(0\) is \(3\). Thus \(P_3(x)=3+3x+3x^2/2+x^3/2\).
(j) Polynomial degree is the greatest exponent with a nonzero coefficient. The missing even powers have zero coefficients, while the \(x^5\) coefficient is nonzero.
(k) Their coefficients \(f^{(k)}(a)/k!\) agree for \(0\le k\le4\), so their fourth-degree Taylor polynomials are identical.
(l) \(P_2(x)=2+3(x-1)-2(x-1)^2\). Therefore \(f(1.05)\approx2+3(0.05)-2(0.05)^2=2.145\).