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 5 · Topic 5.7

Using the Second Derivative Test to Determine Extrema

Classify a critical point using f″ when the test is conclusive.

1. Topic Focus

Use derivatives to prove existence, classify extrema, analyze monotonicity and concavity, sketch graphs, and solve optimization problems.

This topic: Classify a critical point using f″ when the test is conclusive.

2. Key Relationship

\(f'(c)=0,\;f''(c)>0\Rightarrow\text{local min}\)

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

3. Visual Connection

f'(c) = 0f''(c) > 0local minf'(c) = 0f''(c) < 0local maxf'(c) = 0f''(c) = 0inconclusive
Second Derivative Test outcomesAt a stationary point, positive concavity gives a local minimum, negative concavity gives a local maximum, and zero requires another test.

4. Worked Example

If f′(1)=0 and f″(1)<0, the graph is locally concave down and has a local maximum.

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

5. Concept Development

1. What the test determines

The Second Derivative Test classifies a stationary critical number as a local maximum or minimum. It uses the graph's concavity near a horizontal tangent and is often faster than building a complete sign chart for \(f'\).

2. State the hypotheses

Suppose \(f'(c)=0\) and \(f''\) exists and is continuous on an open interval around \(c\). Then the sign of \(f''(c)\) can classify \(f(c)\). The condition \(f'(c)=0\) must be checked before using the test.

3. Why positive means minimum

If \(f''(c)>0\), then \(f'\) is increasing near \(c\). Since \(f'(c)=0\), nearby slopes move from negative to positive, so \(f\) decreases and then increases. Therefore \(f(c)\) is a local minimum.

4. Why negative means maximum

If \(f''(c)<0\), then \(f'\) is decreasing near \(c\). Nearby slopes move from positive to negative, so \(f\) increases and then decreases. Therefore \(f(c)\) is a local maximum.

5. The classification table

\(\begin{array}{c|c|c}f'(c)&f''(c)&\text{conclusion}\\ \hline 0&>0&\text{local minimum}\\ 0&<0&\text{local maximum}\\ 0&=0&\text{inconclusive}\end{array}\)

6. Use the correct order

  1. Find \(f'(x)\).
  2. Solve \(f'(x)=0\) for stationary critical numbers.
  3. Find \(f''(x)\).
  4. Evaluate \(f''\) at each stationary critical number.
  5. Classify when the result is positive or negative.
  6. If a point is requested, calculate \(f(c)\) and report \((c,f(c))\).

7. Zeros of the second derivative are not the candidates

Solving \(f''(x)=0\) locates possible concavity changes, not possible extrema for this test. Extrema candidates come first from \(f'(x)=0\) or from points where \(f'\) is undefined and \(f\) exists.

8. Nondifferentiable critical points need another test

A corner or cusp can be a local extremum, but the Second Derivative Test cannot classify it because \(f'(c)=0\) is not satisfied. Use the First Derivative Test or compare nearby function values instead.

9. Zero means inconclusive

If \(f'(c)=0\) and \(f''(c)=0\), no classification follows. At zero, \(x^4\) has a local minimum, \(-x^4\) has a local maximum, and \(x^3\) has neither. The same second-derivative value permits all three outcomes.

10. Undefined also means the test does not decide

If \(f''(c)\) does not exist, the test is unavailable, not evidence that no extremum exists. Return to the sign of \(f'\), the function's local behavior, or another valid argument.

11. Know when the First Derivative Test is better

The First Derivative Test works at stationary and nondifferentiable critical points and resolves cases where the Second Derivative Test is inconclusive. The second-derivative method is efficient when \(f''(c)\) is easy to evaluate and nonzero.

12. Local is not automatically absolute

The test gives a neighborhood conclusion. To find absolute extrema on a closed interval, also evaluate endpoints and every critical candidate using the Candidates Test. A local minimum can still be higher than an endpoint value.

13. Common errors

  • Solving \(f''=0\) instead of \(f'=0\) for candidates.
  • Using the test when \(f'(c)\ne0\).
  • Calling \(f''(c)=0\) “neither” instead of inconclusive.
  • Forgetting critical points where \(f'\) is undefined.
  • Reporting a local result as an absolute result.
  • Giving only \(c\) when the problem requests the point or value.

6. Detailed Worked Example and Error Check

Example 1: Several stationary critical numbers. Let \(f(x)=x^4-4x^2\).

\(f'(x)=4x(x^2-2),\qquad f''(x)=12x^2-8.\)

The stationary critical numbers are \(0\) and \(\pm\sqrt2\). Since \(f''(0)=-8\), \((0,0)\) is a local maximum. Since \(f''(\pm\sqrt2)=16\), \((\pm\sqrt2,-4)\) are local minima.

Example 2: A cubic with one maximum and one minimum. For \(f(x)=x^3-3x^2\), \(f'(x)=3x(x-2)\) gives \(c=0,2\), and \(f''(x)=6x-6\). Thus \(f''(0)=-6\) gives a local maximum at \((0,0)\), while \(f''(2)=6\) gives a local minimum at \((2,-4)\).

Example 3: Odd-degree polynomial. Let \(f(x)=x^5-5x\). Since \(f'(x)=5(x^4-1)\), the real stationary critical numbers are \(-1\) and \(1\). With \(f''(x)=20x^3\), \(f''(-1)<0\) gives a local maximum at \((-1,4)\), and \(f''(1)>0\) gives a local minimum at \((1,-4)\).

Example 4: Three inconclusive outcomes. Each of \(x^4\), \(-x^4\), and \(x^3\) satisfies \(f'(0)=f''(0)=0\). The Second Derivative Test is inconclusive for all three. A First Derivative Test shows a minimum for \(x^4\), a maximum for \(-x^4\), and neither for \(x^3\).

Example 5: Exponential function. For \(f(x)=e^x-2x\), the equation \(f'(x)=e^x-2=0\) gives \(c=\ln2\). Since \(f''(\ln2)=e^{\ln2}=2>0\), the function has a local minimum at

\(\left(\ln2,\,2-2\ln2\right).\)

Example 6: Trigonometric function. For \(f(x)=\sin x+\cos x\) on \((0,2\pi)\), \(f'(x)=\cos x-\sin x=0\) at \(\pi/4\) and \(5\pi/4\). Since \(f''=-\sin x-\cos x\), the local maximum is \((\pi/4,\sqrt2)\), and the local minimum is \((5\pi/4,-\sqrt2)\).

Example 7: Interpretation in context. A profit model is \(P(q)=-q^3+12q^2-36q+100\) for \(q>0\). Since \(P'(q)=-3(q-2)(q-6)\), the stationary quantities are \(2\) and \(6\). Also \(P''(q)=-6q+24\), so \(P''(2)>0\) gives a local minimum profit of \(P(2)=68\), while \(P''(6)<0\) gives a local maximum profit of \(P(6)=100\).

7. AP Reasoning Routine

State theorem hypotheses, make sign charts on domain intervals, include endpoints when required, and connect derivative signs to function behavior.

  • 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 Second Derivative Test where possible. If it is inconclusive or unavailable, say so and use an appropriate alternative.
(a) Classify all local extrema of \(f(x)=x^3-6x^2+9x\).
(b) Classify all local extrema of \(f(x)=x^4-8x^2\).
(c) Analyze every critical number of \(f(x)=x^4+4x^3\).
(d) Compare the test's result at zero for \(f(x)=x^4\) and \(g(x)=-x^4\), then finish the classifications.
(e) Apply the test to \(f(x)=x^3\) at zero and resolve the result.
(f) Find and classify the stationary point of \(f(x)=e^x-3x\).
(g) Classify the stationary points of \(f(x)=\cos x\) on \((0,2\pi)\).
(h) Suppose \(f'(a)=f'(b)=f'(d)=0\), with \(f''(a)=5\), \(f''(b)=-2\), and \(f''(d)=0\). State every justified conclusion.
(i) Explain what to do when \(f'(c)=0\) but \(f''(c)\) is undefined.
(j) Explain why a local minimum established by the Second Derivative Test need not be the absolute minimum on a closed interval.

Check the solution

In part (a), \(f'(x)=3(x-1)(x-3)\) and \(f''(x)=6x-12\). Since \(f''(1)=-6\), \((1,4)\) is a local maximum; since \(f''(3)=6\), \((3,0)\) is a local minimum. In part (b), \(f'(x)=4x(x-2)(x+2)\) and \(f''(x)=12x^2-16\). Thus \((0,0)\) is a local maximum and \((-2,-16)\) and \((2,-16)\) are local minima. In part (c), \(f'(x)=4x^2(x+3)\), so the critical numbers are \(-3\) and \(0\). Since \(f''(x)=12x(x+2)\), \(f''(-3)=36>0\), giving a local minimum at \((-3,-27)\). At zero the second derivative is zero, so the test is inconclusive; \(f'\) is positive on both sides of zero, making it neither a local maximum nor a local minimum. In part (d), the test is inconclusive for both functions because both second derivatives equal zero at zero. The First Derivative Test or direct comparison shows a local minimum for \(x^4\) and a local maximum for \(-x^4\). In part (e), \(f'(0)=f''(0)=0\), so the test is inconclusive. Because \(f'(x)=3x^2>0\) on both sides, zero is neither type. In part (f), \(f'(x)=e^x-3=0\) at \(x=\ln3\). Since \(f''(\ln3)=3>0\), the local minimum is \((\ln3,3-3\ln3)\). In part (g), \(f'(x)=-\sin x\) vanishes at \(x=\pi\) inside the interval. Since \(f''(\pi)=1>0\), \((\pi,-1)\) is a local minimum. In part (h), \(a\) gives a local minimum, \(b\) gives a local maximum, and the test is inconclusive at \(d\). In part (i), the Second Derivative Test cannot classify the point; analyze the sign of \(f'\) on the two sides or use another local argument. In part (j), the test compares behavior only near the stationary point. Absolute extrema require comparison with all other critical candidates and included endpoints.