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Lesson 66 — Concavity and Inflection Points

Sign of f'': concave up when f'' > 0, down when f'' < 0. Inflection where f'' changes sign. Second derivative test for extrema.

Used in: 2nd Year High School Advanced · Japanese Equiv. Math I/II · German Equiv. Leistungskurs Analysis · University Calculus I

f(x)>0    f concave,f(x)<0    f concave,f changes sign    inflectionf''(x) > 0 \implies f \text{ concave}\uparrow, \quad f''(x) < 0 \implies f \text{ concave}\downarrow, \quad f'' \text{ changes sign} \implies \text{inflection}

The concavity of a curve is determined by the sign of the second derivative: f>0f'' > 0 means concave up (bowl shape), f<0f'' < 0 concave down (cap shape). An inflection point occurs where ff'' changes sign — it is not enough for it to be zero.

Choose your door

Rigorous notation, full derivation, hypotheses

Rigorous Definition and Criteria

Concavity and Convexity

"The function ff is concave up on an interval II if f(x)0f''(x) \geq 0 for all xIx \in I." — OpenStax Calculus Vol. 1 §4.5

Criterion via Second Derivative: If ff is twice differentiable on II:

  • f(x)0f''(x) \geq 0 on II     \iff ff is convex (concave up).
  • f(x)0f''(x) \leq 0 on II     \iff ff is concave (downward).
  • f(x)>0f''(x) > 0 strictly \Rightarrow strict convexity.
f'' > 0 — bowlchord above arcf'' < 0 — capchord below arc

Concave up (f'' > 0): chord lies above the arc. Concave down (f'' < 0): chord lies below the arc.

Inflection Point

Caution: f(x0)=0f''(x_0) = 0 is a necessary but NOT sufficient condition. Canonical counterexample: f(x)=x4f(x) = x^4 has f(0)=0f''(0) = 0 but f0f'' \geq 0 in a neighborhood of 00 — no sign change, thus 00 is not an inflection point.

"If the concavity changes at a point (x0,f(x0))(x_0, f(x_0)), we call this a point of inflection. It must be the case that f(x0)f''(x_0) changes sign." — APEX Calculus §3.4

Second Derivative Test for Local Extrema

Proof for minimum: If f(x0)=0f'(x_0) = 0 and f(x0)>0f''(x_0) > 0, by continuity of ff'' there exists a neighborhood where f(x)>0f''(x) > 0, hence ff' is increasing in this neighborhood. Since f(x0)=0f'(x_0) = 0, we have f<0f' < 0 to the left and f>0f' > 0 to the right of x0x_0 — by the first derivative test, x0x_0 is a local minimum. ∎

Solved Examples

Exercise list

40 exercises · 10 with worked solution (25%)

20 10 4 2 4
  1. Ex. 66.1

    Determine the concavity of f(x)=x2f(x) = x^2 on all of R\mathbb{R}. Is there an inflection point?

  2. Ex. 66.2

    Determine the concavity and inflection points of f(x)=x3f(x) = x^3.

    Show solution
    f=6xf'' = 6x. For x<0x < 0: concave down. For x>0x > 0: concave up. Inflection at x=0x = 0 because ff'' changes sign.
    Show step-by-step (with the why)
    1. Calculate derivatives: f(x)=3x2f'(x) = 3x^2, f(x)=6xf''(x) = 6x.
    2. Zero of ff'': 6x=0x=06x = 0 \Rightarrow x = 0.
    3. Sign: x<0f<0x < 0 \Rightarrow f'' < 0 (cap); x>0f>0x > 0 \Rightarrow f'' > 0 (bowl).
    4. Sign change at x=0x = 0 confirms inflection. Point: (0,0)(0, 0).
    5. Curiosity: the inflection point of x3x^3 is also its only zero — the curve crosses the x-axis exactly where it changes concavity.
  3. Ex. 66.3

    Concavity of f(x)=x4f(x) = x^4. Is there an inflection point at x=0x = 0? Justify using the sign of ff''.

    Show solution
    f=12x20f'' = 12x^2 \geq 0 for all xx. No sign change — no inflection. Concave up on all of R\mathbb{R} (global convexity).
  4. Ex. 66.4

    Concavity of f(x)=exf(x) = e^x on all of R\mathbb{R}. Is there an inflection point?

  5. Ex. 66.5Answer key

    Concavity of f(x)=lnxf(x) = \ln x on (0,)(0, \infty).

  6. Ex. 66.6

    Concavity of f(x)=sinxf(x) = \sin x on [0,2π][0, 2\pi]. Identify the inflection points.

    Show solution
    f=sinxf'' = -\sin x. Zero at x=0,π,2πx = 0, \pi, 2\pi. Inflection points at x=0,π,2πx = 0, \pi, 2\pi (where ff'' changes sign). For x(0,π)x \in (0, \pi): f<0f'' < 0 (cap). For x(π,2π)x \in (\pi, 2\pi): f>0f'' > 0 (bowl).
  7. Ex. 66.7

    Concavity of f(x)=cosxf(x) = \cos x on [0,2π][0, 2\pi]. Inflection points.

  8. Ex. 66.8

    Concavity of f(x)=1/xf(x) = 1/x on the intervals (0,)(0,\infty) and (,0)(-\infty,0).

  9. Ex. 66.9

    Concavity of f(x)=ex2/2f(x) = e^{-x^2/2} (Gaussian). Identify the inflection points.

  10. Ex. 66.10

    Concavity and inflection of f(x)=x33x2+2f(x) = x^3 - 3x^2 + 2.

    Show solution
    f=6x6f'' = 6x - 6. Zero at x=1x = 1. Inflection at (1,f(1))=(1,13+2)=(1,0)(1, f(1)) = (1, 1 - 3 + 2) = (1, 0). Concave down on (,1)(-\infty, 1), up on (1,)(1, \infty).
    Show step-by-step (with the why)
    1. Calculate f(x)=3x26xf'(x) = 3x^2 - 6x and f(x)=6x6f''(x) = 6x - 6.
    2. Zero of ff'': 6x6=0x=16x - 6 = 0 \Rightarrow x = 1.
    3. Sign: x<1f<0x < 1 \Rightarrow f'' < 0; x>1f>0x > 1 \Rightarrow f'' > 0. Change confirmed.
    4. Point: f(1)=13+2=0f(1) = 1 - 3 + 2 = 0. Inflection at (1,0)(1, 0).
    5. Shortcut: for cubic polynomials ax3+bx2+ax^3 + bx^2 + \cdots, the inflection point is always at x=b/(3a)x = -b/(3a) — the center of symmetry of the cubic.
  11. Ex. 66.11Answer key

    Use the ff'' test: classify the extrema of f(x)=x312xf(x) = x^3 - 12x.

    Show solution
    f=3x212=0x=±2f' = 3x^2 - 12 = 0 \Rightarrow x = \pm 2. f=6xf'' = 6x. f(2)=12>0f''(2) = 12 > 0: minimum at (2,16)(2, -16). f(2)=12<0f''(-2) = -12 < 0: maximum at (2,16)(-2, 16).
  12. Ex. 66.12

    Extrema of f(x)=x44x2f(x) = x^4 - 4x^2 via ff'' test.

  13. Ex. 66.13

    Extrema of f(x)=xexf(x) = x e^{-x} via ff''.

    Show solution
    f(x)=ex(1x)=0x=1f'(x) = e^{-x}(1-x) = 0 \Rightarrow x = 1. f(x)=ex(x2)f''(x) = e^{-x}(x-2). f(1)=e1(1)<0f''(1) = e^{-1}(-1) < 0: maximum at (1,e1)(1, e^{-1}).
  14. Ex. 66.14Answer key

    Extrema of f(x)=x2lnxf(x) = x^2 \ln x on (0,)(0, \infty) via ff''.

  15. Ex. 66.15Answer key

    Extrema of f(x)=sinx+12sin(2x)f(x) = \sin x + \frac{1}{2}\sin(2x) on [0,2π][0, 2\pi].

    Show solution
    f(x)=cosx+cos(2x)=0f'(x) = \cos x + \cos(2x) = 0. Using cos(2x)=2cos2x1\cos(2x) = 2\cos^2 x - 1: 2cos2x+cosx1=0cosx=1/22\cos^2 x + \cos x - 1 = 0 \Rightarrow \cos x = 1/2 or 1-1. Critical points: x=π/3,π,5π/3x = \pi/3, \pi, 5\pi/3. Apply ff'' at each.
  16. Ex. 66.16

    Show that f(x)=x4f(x) = x^4 has a minimum at x=0x = 0 despite f(0)=0f''(0) = 0 (inconclusive test).

    Show solution
    Show that x=0x = 0 is a minimum of x4x^4 even with f(0)=0f''(0) = 0: use the fact that f(x)=x40f(x) = x^4 \geq 0 for all xx, and f(0)=0f(0) = 0 is the smallest possible value.
  17. Ex. 66.17

    Show that f(x)=x5f(x) = x^5 has no extremum at x=0x = 0 despite f(0)=0f'(0) = 0.

    Show solution
    For f(x)=x5f(x) = x^5: f(0)=0f'(0) = 0 and f(0)=0f''(0) = 0 (inconclusive). But f(x)=5x40f'(x) = 5x^4 \geq 0 for all xx, with equality only at 00. Therefore ff is increasing in any neighborhood of 00 — no local extremum.
  18. Ex. 66.18

    For f(x)=x2+1/xf(x) = x^2 + 1/x on x>0x > 0: find the minimum and justify with ff''.

  19. Ex. 66.19

    Extrema of f(x)=lnx/xf(x) = \ln x / x on (0,)(0, \infty) via ff''.

    Show solution
    f(x)=(1lnx)/x2=0x=ef'(x) = (1 - \ln x)/x^2 = 0 \Rightarrow x = e. f(e)=(3+2)/e3=1/e3<0f''(e) = (-3 + 2)/e^3 = -1/e^3 < 0: maximum. f(e)=1/ef(e) = 1/e.
  20. Ex. 66.20

    Extrema of f(x)=x1/xf(x) = x^{1/x} on (0,)(0, \infty) (take lnf\ln f before differentiating).

  21. Ex. 66.21

    Cost C(q)=q36q2+9q+100C(q) = q^3 - 6q^2 + 9q + 100. Find the inflection point and interpret it as a change in marginal return.

    Show solution
    C(q)=6q12=0q=2C''(q) = 6q - 12 = 0 \Rightarrow q = 2. For q<2q < 2: decreasing marginal cost (economies of scale). For q>2q > 2: increasing (capacity pressure). Inflection at q=2q = 2 is the point of regime change.
  22. Ex. 66.22Answer key

    Profit π(q)=q3+30q2100q\pi(q) = -q^3 + 30q^2 - 100q. Maximize via π\pi' and confirm with π\pi''.

  23. Ex. 66.23Answer key

    Logistic curve P(t)=K/(1+ert)P(t) = K/(1 + e^{-rt}). Show there is an inflection point at P=K/2P = K/2 (half the carrying capacity).

    Show solution
    For P(t)=K/(1+ert)P(t) = K/(1 + e^{-rt}): P=rP(r2rP/K)P'' = rP(r - 2rP/K). Set to zero: P=K/2P = K/2, which occurs at t=0t = 0 (when centered at zero). Inflection at P=K/2P = K/2: point of maximum population growth.
    Show step-by-step (with the why)
    1. Let P=K/(1+ert)P = K/(1+e^{-rt}). Calculate P=rP(1P/K)P' = rP(1 - P/K) (logistic growth rate).
    2. Differentiate again: P=rP(12P/K)P'' = r P' (1 - 2P/K).
    3. Set to zero: P=0P = 0 (trivial) or P=K/2P = K/2.
    4. At P=K/2P = K/2: PP'' changes sign — inflection.
    5. Note: The inflection point of the logistic curve corresponds to the maximum growth rate — the "turning point" of an epidemic or market expansion.
  24. Ex. 66.24

    Potential energy U(x)=cosxU(x) = -\cos x (pendulum). Find stable and unstable equilibria using UU''.

  25. Ex. 66.25

    Harmonic spring: U(x)=12kx2U(x) = \frac{1}{2}kx^2. Show x=0x = 0 is a stable equilibrium using UU''.

    Show solution
    U(x)=12kx2U(x) = \frac{1}{2}kx^2. U(x)=kx=0U'(x) = kx = 0 at x=0x = 0. U(x)=k>0U''(x) = k > 0: concave up. Minimum at x=0x = 0 — stable equilibrium. Natural oscillation frequency: ω=k/m\omega = \sqrt{k/m}.
  26. Ex. 66.26

    Bernoulli entropy H(p)=plnp(1p)ln(1p)H(p) = -p\ln p - (1-p)\ln(1-p). Show H<0H'' < 0 and that the maximum is at p=1/2p = 1/2.

  27. Ex. 66.27Answer key

    Learning curve L(t)=1ektL(t) = 1 - e^{-kt}. Determine its concavity. What does it say about the speed of learning?

    Show solution
    Learning curve: L(t)=1ektL(t) = 1 - e^{-kt}. L=k2ekt<0L'' = -k^2 e^{-kt} < 0. Concave down: learning gains diminish over time (diminishing returns). No inflection.
  28. Ex. 66.28

    In an epidemic, the peak of new cases occurs at the inflection point of the cumulative case curve f(t)f(t). Justify geometrically and via ff''.

  29. Ex. 66.29

    Utility U(W)=lnWU(W) = \ln W is concave. Explain how Jensen's inequality implies risk aversion for this investor.

    Show solution
    Utility $U(W) = \ln W$: U=1/W2<0U'' = -1/W^2 < 0 — concave down. By Jensen: E[U(W)]U(E[W])E[U(W)] \leq U(E[W]). This means the agent prefers the guaranteed expected value to the lottery — definition of risk aversion.
  30. Ex. 66.30

    Why does the linear regression loss function have a unique global minimum? Justify using convexity.

  31. Ex. 66.31

    What is the correct condition for x0x_0 to be an inflection point of ff?

    Select the correct option
    Select an option first
    Show solution
    The definition of an inflection point requires a sign change of ff''. Having f=0f'' = 0 without a sign change (like for x4x^4 at 0) does not constitute an inflection.
  32. Ex. 66.32

    Prove that the sum of two convex functions is convex, using the definition via ff''.

    Show solution
    Sum: (f+g)=f+g(f+g)'' = f'' + g''. If f0f'' \geq 0 and g0g'' \geq 0, then (f+g)0(f+g)'' \geq 0. Thus f+gf+g is convex.
  33. Ex. 66.33

    Show that ff convex on II implies the midpoint inequality: f ⁣(x+y2)f(x)+f(y)2f\!\left(\frac{x+y}{2}\right) \leq \frac{f(x)+f(y)}{2}.

    Show solution
    Show that f((x+y)/2)(f(x)+f(y))/2f((x+y)/2) \leq (f(x)+f(y))/2: use the definition of convexity with t=1/2t = 1/2. Geometrically: the midpoint of the segment lies above the midpoint of the graph.
  34. Ex. 66.34

    Why is f(x0)=0f''(x_0) = 0 not sufficient to guarantee an inflection point? Give a concrete counterexample.

    Show solution
    Provide the counterexample $f(x) = x^4$: f(0)=0f''(0) = 0 but f0f'' \geq 0 around $0$ — no sign change. Thus x=0x = 0 is not an inflection point despite f=0f'' = 0.
  35. Ex. 66.35

    Show that ln\ln is concave on (0,)(0,\infty) and use it to prove the AM-GM inequality: (x+y)/2xy(x+y)/2 \geq \sqrt{xy} for x,y>0x, y > 0.

    Show solution
    ln\ln is concave: ln((x+y)/2)(lnx+lny)/2=lnxy\ln((x+y)/2) \geq (\ln x + \ln y)/2 = \ln\sqrt{xy}. Applying the exponential: (x+y)/2xy(x+y)/2 \geq \sqrt{xy}. QED.
  36. Ex. 66.36Answer key

    Huber function L(x)=x2/2L(x) = x^2/2 if x1|x| \leq 1; x1/2|x| - 1/2 otherwise. Is it convex? Where is LL'' discontinuous?

    Show solution
    Huber loss: L(x)=x2/2L(x) = x^2/2 if x1|x| \leq 1, x1/2|x| - 1/2 otherwise. Second derivative: L=1L'' = 1 for x<1|x| < 1, L=0L'' = 0 for x>1|x| > 1. LL'' does not exist at x=±1x = \pm 1. It is convex (non-negative). It is not strictly convex.
  37. Ex. 66.37

    Prove the second derivative test using the Taylor polynomial of order 2.

    Show solution
    Taylor expansion of order 2 around x0x_0: f(x)f(x0)+f(x0)(xx0)+f(x0)2(xx0)2f(x) \approx f(x_0) + f'(x_0)(x - x_0) + \frac{f''(x_0)}{2}(x-x_0)^2. With f(x0)=0f'(x_0) = 0: f(x)f(x0)f(x0)2(xx0)2f(x) - f(x_0) \approx \frac{f''(x_0)}{2}(x-x_0)^2. If f(x0)>0f''(x_0) > 0: the right side is positive near x0x_0, so f(x)>f(x0)f(x) > f(x_0) — local minimum. Similarly for f<0f'' < 0.
  38. Ex. 66.38Answer key

    Prove Jensen's inequality for two points: f(tx1+(1t)x2)tf(x1)+(1t)f(x2)f(tx_1 + (1-t)x_2) \leq tf(x_1) + (1-t)f(x_2) — directly from the definition of convexity.

    Show solution
    Definition of convexity: f(tx1+(1t)x2)tf(x1)+(1t)f(x2)f(tx_1 + (1-t)x_2) \leq tf(x_1) + (1-t)f(x_2) for all t[0,1]t \in [0,1]. With t=1/2t = 1/2 and properties of integrals/probability, the general Jensen inequality can be deduced by induction or continuity.
  39. Ex. 66.39

    Prove that a convex function on an open interval is continuous on the interior.

    Show solution
    Let ff be convex on an open interval II. For x0Ix_0 \in I, the quotient function (f(x)f(x0))/(xx0)(f(x) - f(x_0))/(x - x_0) is increasing in xx. This implies that the one-sided limits exist and are finite, hence ff is continuous at x0x_0.
  40. Ex. 66.40Answer key

    Prove that ff is convex if and only if its graph lies above every tangent line: f(y)f(x)+f(x)(yx)f(y) \geq f(x) + f'(x)(y-x) for all x,yx, y.

    Show solution
    From the Taylor remainder of order 1 with expansion point at xx: f(y)f(x)+f(x)(yx)f(y) \geq f(x) + f'(x)(y - x) for all yy, since R1(y)=f(ξ)(yx)2/20R_1(y) = f''(\xi)(y-x)^2/2 \geq 0. This is equivalent to convexity (support by the tangent).

Sources

  • Active Calculus — Boelkins · 2024 · §3.1 Using Derivatives to Identify Extreme Values · CC-BY-NC-SA. Primary source.
  • Calculus Volume 1 — OpenStax · 2016 · §4.5 Derivatives and the Shape of a Graph · CC-BY-NC-SA.
  • APEX Calculus — Hartman et al. · 2024 · v5.0 · §3.4 Concavity and the Second Derivative Test · CC-BY-NC.

Updated on 2024-07-24 · Author(s): Clube da Matemática

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