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 10.1 · BC Only

Defining Convergent and Divergent Infinite Series

Define an infinite series through its partial-sum sequence and distinguish finite accumulation from individual terms.

1. Topic Focus

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

This topic: Define an infinite series through its partial-sum sequence and distinguish finite accumulation from individual terms.

2. Key Relationship

\(S_N=\sum_{n=1}^N a_n,\qquad \sum_{n=1}^{\infty}a_n=S\iff\lim\limits_{N\to\infty}S_N=S\)

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

3. Visual Connection

terms versus partial sums
Series definitionConvergence belongs to the partial-sum sequence; a zero term limit alone cannot establish it.

4. Worked Example

Convergence asks whether partial sums approach one finite value; small terms alone do not settle that question.

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. An infinite series is not evaluated by completing infinitely many additions. It is defined by a limit of ordinary finite sums. This definition is the foundation for every convergence test in Unit 10.

Sequence terms versus a series

A sequence is an ordered list \(a_1,a_2,a_3,\ldots\). A series is the accumulation of those terms:

\(\sum_{n=1}^{\infty}a_n=a_1+a_2+a_3+\cdots.\)

The symbol \(n\) is a dummy index. Changing its letter does not change the series, but changing the starting index can add or remove terms.

Partial sums make the definition precise

The \(N\)th partial sum is the finite sum of the first \(N\) terms:

\(S_N=\sum_{n=1}^{N}a_n=a_1+a_2+\cdots+a_N.\)

The values \(S_1,S_2,S_3,\ldots\) form a new sequence called the sequence of partial sums. Do not confuse \(a_N\), the newest term, with \(S_N\), the total accumulated through that term.

Definition of convergence

\(\boxed{\sum_{n=1}^{\infty}a_n=S\quad\Longleftrightarrow\quad\lim\limits_{N\to\infty}S_N=S}\)

The series converges only when the partial sums approach one finite real number. That limit is called the sum of the series. If the partial-sum limit does not exist as a finite number, the series diverges.

Different ways a series can diverge

  • Growth to \(+\infty\): partial sums increase without bound.
  • Growth to \(-\infty\): partial sums decrease without bound.
  • Oscillation: partial sums alternate between separated values.
  • Irregular behavior: partial sums remain unsettled without approaching one limit.

“Diverges” does not mean that every divergent series has sum infinity. Infinity is not a finite series sum.

Recover terms from partial sums

Since consecutive partial sums differ by the newest term,

\(a_1=S_1,\qquad a_N=S_N-S_{N-1}\quad(N\ge2).\)

This relationship allows a problem to specify a series indirectly through a formula, table, or graph for \(S_N\).

A necessary condition for convergence

If \(S_N\to S\), then

\(a_N=S_N-S_{N-1}\longrightarrow S-S=0.\)

Therefore every convergent series must satisfy \(a_N\to0\). The converse is false: terms can approach zero too slowly for their accumulated partial sums to converge. Topic 10.3 develops this divergence test formally.

Telescoping partial sums

Some terms can be rewritten as differences \(a_n=b_n-b_{n+1}\). In a finite partial sum, most intermediate quantities cancel:

\(S_N=\sum_{n=1}^{N}(b_n-b_{n+1})=b_1-b_{N+1}.\)

The infinite series is then decided by the limit of the remaining boundary expression, not by informal cancellation across an unfinished infinite sum.

Starting index and finite changes

Adding, deleting, or changing finitely many terms changes the numerical sum of a convergent series but does not change whether its tail converges. For an integer \(m>1\),

\(\sum_{n=m}^{\infty}a_n=\sum_{n=1}^{\infty}a_n-\sum_{n=1}^{m-1}a_n\)

whenever the original series converges. This principle is useful when reindexing or isolating a tail.

Linearity for convergent series

If \(\sum a_n=A\) and \(\sum b_n=B\) both converge, then for constants \(c,d\),

\(\sum_{n=1}^{\infty}(ca_n+db_n)=cA+dB.\)

The convergence assumptions matter. Algebraic combinations of divergent series cannot generally be manipulated as though they had finite sums.

Tables and graphs of partial sums

A table of \(S_N\) suggests convergence when the values settle toward one number, but a finite table alone is not proof. A graph of partial sums should be read as a discrete sequence: convergence means the plotted heights approach one horizontal level as \(N\) grows.

Partial sums as approximations

When a series converges to \(S\), \(S_N\) is a finite approximation and

\(R_N=S-S_N\)

is the remainder after \(N\) terms. This topic defines the approximation; later topics provide practical error bounds for specific kinds of series.

Definition-first checklist

  1. Identify the term sequence \(a_n\) and starting index.
  2. Write or determine the finite partial sum \(S_N\).
  3. Simplify \(S_N\) before taking a limit.
  4. Evaluate \(\lim\limits_{N\to\infty}S_N\).
  5. Conclude “converges to \(S\)” only for a finite limit; otherwise state how it diverges.
  6. Keep conclusions about \(a_n\) separate from conclusions about \(S_N\).

6. Detailed Worked Example and Error Check

Example 1: Convergence from an explicit partial sum

Suppose \(S_N=N/(N+1)\). Then

\(\lim\limits_{N\to\infty}S_N=\lim\limits_{N\to\infty}\frac{N}{N+1}=1.\)

Therefore the series converges and its sum is \(1\).

Example 2: Oscillating partial sums

If \(S_N=(-1)^N\), then the even partial sums equal \(1\) and the odd partial sums equal \(-1\). The sequence has no limit, so the series diverges by oscillation.

Example 3: Unbounded partial sums

If \(S_N=\ln(N+1)\), then \(S_N\to+\infty\). The series diverges; it does not have “sum infinity” under the definition of convergence.

Example 4: A basic telescoping series

Use partial fractions:

\(\frac1{n(n+1)}=\frac1n-\frac1{n+1}.\)

The finite partial sum is

\(\begin{aligned}S_N&=\sum_{n=1}^{N}\left(\frac1n-\frac1{n+1}\right)\\&=1-\frac1{N+1}.\end{aligned}\)

Thus \(S_N\to1\), so \(\sum_{n=1}^{\infty}1/[n(n+1)]=1\).

Example 5: Two uncanceled terms at each end

For

\(\frac{2}{(n+1)(n+3)}=\frac1{n+1}-\frac1{n+3},\)

the partial sum is

\(S_N=\frac12+\frac13-\frac1{N+2}-\frac1{N+3}.\)

Therefore the series converges to \(1/2+1/3=5/6\).

Example 6: Recover the terms from \(S_N\)

Let \(S_N=3-2/N\). The first term is \(a_1=S_1=1\). For \(N\ge2\),

\(\begin{aligned}a_N&=S_N-S_{N-1}\\&=\left(3-\frac2N\right)-\left(3-\frac2{N-1}\right)=\frac{2}{N(N-1)}.\end{aligned}\)

The series sum is \(\lim S_N=3\). The separate formula for \(a_1\) is essential.

Example 7: Remove finitely many terms

Suppose \(\sum_{n=1}^{\infty}a_n=6\), with \(a_1=2\) and \(a_2=-1\). Then

\(\sum_{n=3}^{\infty}a_n=6-(2-1)=5.\)

Removing the first two terms changes the sum from \(6\) to \(5\), but the remaining tail still converges.

Example 8: Terms approach zero but the series diverges

For the harmonic series, \(a_n=1/n\to0\). However, grouping terms in partial sums at powers of two gives

\(S_{2^m}\ge1+\frac{m}{2}.\)

These partial sums are unbounded, so \(\sum1/n\) diverges. The condition \(a_n\to0\) was necessary but not sufficient.

Example 9: Terms and partial sums both oscillate

For \(\sum_{n=1}^{\infty}(-1)^n\), the terms alternate between \(-1\) and \(1\), while

\(S_N=\begin{cases}-1,&N\text{ odd},\\0,&N\text{ even}.\end{cases}\)

The partial sums do not settle, so the series diverges.

Example 10: Infer a partial-sum pattern from a table

Suppose the first partial sums are \(1/2,3/4,7/8,15/16\). The pattern

\(S_N=1-\frac1{2^N}\)

fits the table and has limit \(1\). If this formula is established for every \(N\), the series converges to \(1\). The table alone only suggests the pattern.

Common errors

  • Calling \(a_N\) the partial sum.
  • Treating the infinity symbol as a last index that can be substituted.
  • Concluding convergence merely because \(a_N\to0\).
  • Calling unbounded growth a finite sum.
  • Inferring convergence from a short decimal table without a formula or theorem.
  • Telescoping an infinite expression without first writing \(S_N\).
  • Using \(a_N=S_N-S_{N-1}\) at \(N=1\) without defining \(S_0\).
  • Forgetting that removing initial terms changes the sum even though it preserves convergence.
  • Combining divergent series through ordinary sum laws.
  • Confusing a sequence limit \(\lim a_n\) with the series sum \(\lim S_N\).

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

Use the definition through partial sums unless another instruction is given.
(a) For \(a_n=2n-1\), write the first four terms and compute \(S_4\).
(b) A series has \(S_N=(2N+1)/(N+1)\). Determine convergence and its sum.
(c) A series has \(S_N=(-1)^N/N\). Determine convergence and its sum.
(d) A series has \(S_N=\sin(N\pi/2)\). Determine whether it converges or diverges.
(e) A series has \(S_N=\sqrt N\). Describe its divergence.
(f) Evaluate \(\sum_{n=1}^{\infty}1/[n(n+2)]\) by finding a formula for \(S_N\).
(g) If \(S_N=5-3/2^N\), find the series sum, \(a_1\), and a formula for \(a_N\) when \(N\ge2\).
(h) Suppose \(\sum_{n=1}^{\infty}a_n=10\), \(a_1=4\), \(a_2=-2\), and \(a_3=1\). Find \(\sum_{n=4}^{\infty}a_n\).
(i) Explain why \(a_n\to0\) cannot by itself prove that \(\sum a_n\) converges.
(j) If \(S_N=L+(-1)^N/N\), determine the sum of the series.
(k) Given convergent series \(\sum a_n=4\) and \(\sum b_n=-2\), find \(\sum(3a_n-2b_n)\).
(l) The partial sums are \(S_1=0.6,S_2=0.76,S_3=0.824,S_4=0.8496\). Explain what the data can and cannot establish about convergence.

Check the solution

(a) The terms are \(1,3,5,7\), so \(S_4=16\).
(b) \(\lim\limits_{N\to\infty}(2N+1)/(N+1)=2\), so the series converges to \(2\).
(c) Since \((-1)^N/N\to0\), the partial sums converge to \(0\); therefore the series converges and its sum is \(0\).
(d) The partial sums repeat \(1,0,-1,0,\ldots\), so they do not approach one value. The series diverges by oscillation.
(e) Since \(\sqrt N\to+\infty\), the partial sums are unbounded and the series diverges.
(f) Since \(1/[n(n+2)]=\tfrac12(1/n-1/(n+2))\), \(S_N=\tfrac12(1+1/2-1/(N+1)-1/(N+2))\). Hence the sum is \(3/4\).
(g) The sum is \(\lim S_N=5\). Also \(a_1=S_1=7/2\), and for \(N\ge2\), \(a_N=S_N-S_{N-1}=3/2^N\).
(h) The first three terms sum to \(4-2+1=3\), so the tail sum is \(10-3=7\).
(i) Convergence forces terms toward zero, but the converse fails. For example, \(1/n\to0\) while the harmonic partial sums are unbounded.
(j) Because \((-1)^N/N\to0\), \(S_N\to L\). The series converges to \(L\).
(k) Linearity gives \(3(4)-2(-2)=16\).
(l) The values appear to settle and may suggest a limit, but finitely many partial sums cannot prove convergence or identify an exact sum. A formula, bound, or valid convergence theorem is still needed.