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# Lesson 18: Maximum and Minimum Values (Section 041 slides)

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There are various reasons why we would want to find the extreme (maximum and minimum values) of a function. Fermat's Theorem tells us we can find local extreme points by looking at critical points. This process is known as the Closed Interval Method.

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### Transcript of "Lesson 18: Maximum and Minimum Values (Section 041 slides)"

1. 1. Section 4.1 Maximum and Minimum Values V63.0121.041, Calculus I New York University November 8, 2010Announcements Quiz 4 on Sections 3.3, 3.4, 3.5, and 3.7 next week (November 16, 18, or 19) . . . . . .
2. 2. Announcements Quiz 4 on Sections 3.3, 3.4, 3.5, and 3.7 next week (November 16, 18, or 19) . . . . . . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 2 / 34
3. 3. Objectives Understand and be able to explain the statement of the Extreme Value Theorem. Understand and be able to explain the statement of Fermat’s Theorem. Use the Closed Interval Method to find the extreme values of a function defined on a closed interval. . . . . . . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 3 / 34
4. 4. OutlineIntroductionThe Extreme Value TheoremFermat’s Theorem (not the last one) Tangent: Fermat’s Last TheoremThe Closed Interval MethodExamples . . . . . . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 4 / 34
5. 5. Optimize.
6. 6. Why go to the extremes? Rationally speaking, it is advantageous to find the extreme values of a function (maximize profit, minimize costs, etc.) Pierre-Louis Maupertuis V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values (1698–1759) 8, 2010 November 6 / 34
7. 7. Design.Image credit: Jason Tromm . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 7 / 34
8. 8. Why go to the extremes? Rationally speaking, it is advantageous to find the extreme values of a function (maximize profit, minimize costs, etc.) Many laws of science are derived from minimizing principles. Pierre-Louis Maupertuis V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values (1698–1759) 8, 2010 November 8 / 34
9. 9. Optics.Image credit: jacreative . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 9 / 34
10. 10. Why go to the extremes? Rationally speaking, it is advantageous to find the extreme values of a function (maximize profit, minimize costs, etc.) Many laws of science are derived from minimizing principles. Maupertuis’ principle: “Action is minimized through the wisdom of God.” Pierre-Louis Maupertuis V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values (1698–1759) 8, 2010 November 10 / 34
11. 11. OutlineIntroductionThe Extreme Value TheoremFermat’s Theorem (not the last one) Tangent: Fermat’s Last TheoremThe Closed Interval MethodExamples V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 11 / 34
12. 12. Extreme points and values Definition Let f have domain D. ..Image credit: Patrick Q V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 12 / 34
13. 13. Extreme points and values Definition Let f have domain D. The function f has an absolute maximum (or global maximum) (respectively, absolute minimum) at c if f(c) ≥ f(x) (respectively, f(c) ≤ f(x)) for all x in D ..Image credit: Patrick Q V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 12 / 34
14. 14. Extreme points and values Definition Let f have domain D. The function f has an absolute maximum (or global maximum) (respectively, absolute minimum) at c if f(c) ≥ f(x) (respectively, f(c) ≤ f(x)) for all x in D The number f(c) is called the maximum value (respectively, minimum value) of f on D. ..Image credit: Patrick Q V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 12 / 34
15. 15. Extreme points and values Definition Let f have domain D. The function f has an absolute maximum (or global maximum) (respectively, absolute minimum) at c if f(c) ≥ f(x) (respectively, f(c) ≤ f(x)) for all x in D The number f(c) is called the maximum value (respectively, minimum value) of f on D. . An extremum is either a maximum or a minimum. An extreme value is either a.mage credit: Patrick Q value or minimum value.I maximum V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 12 / 34
16. 16. The Extreme Value TheoremTheorem (The Extreme Value Theorem)Let f be a function which is continuous on the closed interval [a, b].Then f attains an absolute maximum value f(c) and an absoluteminimum value f(d) at numbers c and d in [a, b]. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 13 / 34
17. 17. The Extreme Value TheoremTheorem (The Extreme Value Theorem)Let f be a function which is continuous on the closed interval [a, b].Then f attains an absolute maximum value f(c) and an absoluteminimum value f(d) at numbers c and d in [a, b]. . . . . a . b . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 13 / 34
18. 18. The Extreme Value Theorem Theorem (The Extreme Value Theorem) Let f be a function which is continuous on the closed interval [a, b]. Then f attains an absolute maximum value f(c) and an absolute minimum value f(d) at numbers c and d in [a, b].. maximum .(c) f . value. . minimum .(d) f . value . . .. a . d c b . minimum maximum V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 13 / 34
19. 19. No proof of EVT forthcoming This theorem is very hard to prove without using technical facts about continuous functions and closed intervals. But we can show the importance of each of the hypotheses. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 14 / 34
20. 20. Bad Example #1ExampleConsider the function { x 0≤x<1 f(x) = x − 2 1 ≤ x ≤ 2. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 15 / 34
21. 21. Bad Example #1ExampleConsider the function . { x 0≤x<1 f(x) = . . | . x − 2 1 ≤ x ≤ 2. 1 . . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 15 / 34
22. 22. Bad Example #1ExampleConsider the function . { x 0≤x<1 f(x) = . . | . x − 2 1 ≤ x ≤ 2. 1 . .Then although values of f(x) get arbitrarily close to 1 and never biggerthan 1, 1 is not the maximum value of f on [0, 1] because it is neverachieved. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 15 / 34
23. 23. Bad Example #1ExampleConsider the function . { x 0≤x<1 f(x) = . . | . x − 2 1 ≤ x ≤ 2. 1 . .Then although values of f(x) get arbitrarily close to 1 and never biggerthan 1, 1 is not the maximum value of f on [0, 1] because it is neverachieved. This does not violate EVT because f is not continuous. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 15 / 34
24. 24. Bad Example #2ExampleConsider the function f(x) = x restricted to the interval [0, 1). V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 16 / 34
25. 25. Bad Example #2ExampleConsider the function f(x) = x restricted to the interval [0, 1). . . . | 1 . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 16 / 34
26. 26. Bad Example #2ExampleConsider the function f(x) = x restricted to the interval [0, 1). . . . | 1 .There is still no maximum value (values get arbitrarily close to 1 but donot achieve it). V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 16 / 34
27. 27. Bad Example #2ExampleConsider the function f(x) = x restricted to the interval [0, 1). . . . | 1 .There is still no maximum value (values get arbitrarily close to 1 but donot achieve it). This does not violate EVT because the domain is notclosed. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 16 / 34
28. 28. Final Bad ExampleExample 1Consider the function f(x) = is continuous on the closed interval x[1, ∞). V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 17 / 34
29. 29. Final Bad ExampleExample 1Consider the function f(x) = is continuous on the closed interval x[1, ∞). . . . 1 . V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 17 / 34
30. 30. Final Bad ExampleExample 1Consider the function f(x) = is continuous on the closed interval x[1, ∞). . . . 1 .There is no minimum value (values get arbitrarily close to 0 but do notachieve it). V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 17 / 34
31. 31. Final Bad ExampleExample 1Consider the function f(x) = is continuous on the closed interval x[1, ∞). . . . 1 .There is no minimum value (values get arbitrarily close to 0 but do notachieve it). This does not violate EVT because the domain is notbounded. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 17 / 34
32. 32. OutlineIntroductionThe Extreme Value TheoremFermat’s Theorem (not the last one) Tangent: Fermat’s Last TheoremThe Closed Interval MethodExamples V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 18 / 34
33. 33. Local extrema.Definition A function f has a local maximum or relative maximum at c if f(c) ≥ f(x) when x is near c. This means that f(c) ≥ f(x) for all x in some open interval containing c. Similarly, f has a local minimum at c if f(c) ≤ f(x) when x is near c.. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 19 / 34
34. 34. Local extrema.Definition A function f has a local maximum or relative maximum at c if f(c) ≥ f(x) when x is near c. This means that f(c) ≥ f(x) for all x in some open interval containing c. Similarly, f has a local minimum at c if f(c) ≤ f(x) when x is near c. . . . . .|. . . . | a . local local b . maximum minimum. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 19 / 34
35. 35. Local extrema. So a local extremum must be inside the domain of f (not on the end). A global extremum that is inside the domain is a local extremum. . . . . .|. . . .. | a . local local and global . global b maximum min max. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 19 / 34
36. 36. Fermats TheoremTheorem (Fermat’s Theorem)Suppose f has a local extremum at c and f is differentiable at c. Thenf′ (c) = 0. . . . . ... | . . | a . local local b . maximum minimum V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 21 / 34
37. 37. Fermats TheoremTheorem (Fermat’s Theorem)Suppose f has a local extremum at c and f is differentiable at c. Thenf′ (c) = 0. . . . . ... | . . | a . local local b . maximum minimum V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 21 / 34
38. 38. Sketch of proof of Fermats TheoremSuppose that f has a local maximum at c. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 22 / 34
39. 39. Sketch of proof of Fermats TheoremSuppose that f has a local maximum at c. If x is slightly greater than c, f(x) ≤ f(c). This means f(x) − f(c) ≤0 x−c V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 22 / 34
40. 40. Sketch of proof of Fermats TheoremSuppose that f has a local maximum at c. If x is slightly greater than c, f(x) ≤ f(c). This means f(x) − f(c) f(x) − f(c) ≤ 0 =⇒ lim+ ≤0 x−c x→c x−c V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 22 / 34
41. 41. Sketch of proof of Fermats TheoremSuppose that f has a local maximum at c. If x is slightly greater than c, f(x) ≤ f(c). This means f(x) − f(c) f(x) − f(c) ≤ 0 =⇒ lim+ ≤0 x−c x→c x−c The same will be true on the other end: if x is slightly less than c, f(x) ≤ f(c). This means f(x) − f(c) ≥0 x−c V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 22 / 34
42. 42. Sketch of proof of Fermats TheoremSuppose that f has a local maximum at c. If x is slightly greater than c, f(x) ≤ f(c). This means f(x) − f(c) f(x) − f(c) ≤ 0 =⇒ lim+ ≤0 x−c x→c x−c The same will be true on the other end: if x is slightly less than c, f(x) ≤ f(c). This means f(x) − f(c) f(x) − f(c) ≥ 0 =⇒ lim ≥0 x−c x→c − x−c V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 22 / 34
43. 43. Sketch of proof of Fermats TheoremSuppose that f has a local maximum at c. If x is slightly greater than c, f(x) ≤ f(c). This means f(x) − f(c) f(x) − f(c) ≤ 0 =⇒ lim+ ≤0 x−c x→c x−c The same will be true on the other end: if x is slightly less than c, f(x) ≤ f(c). This means f(x) − f(c) f(x) − f(c) ≥ 0 =⇒ lim ≥0 x−c x→c − x−c f(x) − f(c) Since the limit f′ (c) = lim exists, it must be 0. x→c x−c V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 22 / 34
44. 44. Meet the Mathematician: Pierre de Fermat 1601–1665 Lawyer and number theorist Proved many theorems, didn’t quite prove his last one V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 23 / 34
45. 45. Tangent: Fermats Last Theorem Plenty of solutions to x2 + y2 = z2 among positive whole numbers (e.g., x = 3, y = 4, z = 5) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 24 / 34
46. 46. Tangent: Fermats Last Theorem Plenty of solutions to x2 + y2 = z2 among positive whole numbers (e.g., x = 3, y = 4, z = 5) No solutions to x3 + y3 = z3 among positive whole numbers V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 24 / 34
47. 47. Tangent: Fermats Last Theorem Plenty of solutions to x2 + y2 = z2 among positive whole numbers (e.g., x = 3, y = 4, z = 5) No solutions to x3 + y3 = z3 among positive whole numbers Fermat claimed no solutions to xn + yn = zn but didn’t write down his proof V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 24 / 34
48. 48. Tangent: Fermats Last Theorem Plenty of solutions to x2 + y2 = z2 among positive whole numbers (e.g., x = 3, y = 4, z = 5) No solutions to x3 + y3 = z3 among positive whole numbers Fermat claimed no solutions to xn + yn = zn but didn’t write down his proof Not solved until 1998! (Taylor–Wiles) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 24 / 34
49. 49. OutlineIntroductionThe Extreme Value TheoremFermat’s Theorem (not the last one) Tangent: Fermat’s Last TheoremThe Closed Interval MethodExamples V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 25 / 34
50. 50. Flowchart for placing extremaThanks to FermatSuppose f is a continuous function on the closed, bounded interval[a, b], and c is a global maximum point. . . . c is a start local max . . . Is c an Is f diff’ble f is not n .o n .o endpoint? at c? diff at c y . es y . es . . c = a or f′ (c) = 0 c = b V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 26 / 34
51. 51. The Closed Interval MethodThis means to find the maximum value of f on [a, b], we need to: Evaluate f at the endpoints a and b Evaluate f at the critical points or critical numbers x where either f′ (x) = 0 or f is not differentiable at x. The points with the largest function value are the global maximum points The points with the smallest or most negative function value are the global minimum points. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 27 / 34
52. 52. OutlineIntroductionThe Extreme Value TheoremFermat’s Theorem (not the last one) Tangent: Fermat’s Last TheoremThe Closed Interval MethodExamples V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 28 / 34
53. 53. Extreme values of a linear functionExampleFind the extreme values of f(x) = 2x − 5 on [−1, 2]. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 29 / 34
54. 54. Extreme values of a linear functionExampleFind the extreme values of f(x) = 2x − 5 on [−1, 2].SolutionSince f′ (x) = 2, which is never zero, we have no critical points and weneed only investigate the endpoints: f(−1) = 2(−1) − 5 = −7 f(2) = 2(2) − 5 = −1 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 29 / 34
55. 55. Extreme values of a linear functionExampleFind the extreme values of f(x) = 2x − 5 on [−1, 2].SolutionSince f′ (x) = 2, which is never zero, we have no critical points and weneed only investigate the endpoints: f(−1) = 2(−1) − 5 = −7 f(2) = 2(2) − 5 = −1So The absolute minimum (point) is at −1; the minimum value is −7. The absolute maximum (point) is at 2; the maximum value is −1. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 29 / 34
56. 56. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2]. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
57. 57. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2].SolutionWe have f′ (x) = 2x, which is zero when x = 0. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
58. 58. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2].SolutionWe have f′ (x) = 2x, which is zero when x = 0. So our points to checkare: f(−1) = f(0) = f(2) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
59. 59. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2].SolutionWe have f′ (x) = 2x, which is zero when x = 0. So our points to checkare: f(−1) = 0 f(0) = f(2) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
60. 60. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2].SolutionWe have f′ (x) = 2x, which is zero when x = 0. So our points to checkare: f(−1) = 0 f(0) = − 1 f(2) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
61. 61. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2].SolutionWe have f′ (x) = 2x, which is zero when x = 0. So our points to checkare: f(−1) = 0 f(0) = − 1 f(2) = 3 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
62. 62. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2].SolutionWe have f′ (x) = 2x, which is zero when x = 0. So our points to checkare: f(−1) = 0 f(0) = − 1 (absolute min) f(2) = 3 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
63. 63. Extreme values of a quadratic functionExampleFind the extreme values of f(x) = x2 − 1 on [−1, 2].SolutionWe have f′ (x) = 2x, which is zero when x = 0. So our points to checkare: f(−1) = 0 f(0) = − 1 (absolute min) f(2) = 3 (absolute max) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 30 / 34
64. 64. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2]. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
65. 65. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
66. 66. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
67. 67. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
68. 68. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 f(0) = 1 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
69. 69. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 f(0) = 1 f(1) = 0 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
70. 70. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 f(0) = 1 f(1) = 0 f(2) = 5 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
71. 71. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 (global min) f(0) = 1 f(1) = 0 f(2) = 5 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
72. 72. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 (global min) f(0) = 1 f(1) = 0 f(2) = 5 (global max) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
73. 73. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 (global min) f(0) = 1 (local max) f(1) = 0 f(2) = 5 (global max) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
74. 74. Extreme values of a cubic functionExampleFind the extreme values of f(x) = 2x3 − 3x2 + 1 on [−1, 2].SolutionSince f′ (x) = 6x2 − 6x = 6x(x − 1), we have critical points at x = 0 andx = 1. The values to check are f(−1) = − 4 (global min) f(0) = 1 (local max) f(1) = 0 (local min) f(2) = 5 (global max) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 31 / 34
75. 75. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2]. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
76. 76. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
77. 77. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
78. 78. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = 1 f(−4/5) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
79. 79. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = 1 f(−4/5) = 1.0341 f(0) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
80. 80. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = 1 f(−4/5) = 1.0341 f(0) = 0 f(2) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
81. 81. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = 1 f(−4/5) = 1.0341 f(0) = 0 f(2) = 6.3496 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
82. 82. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = 1 f(−4/5) = 1.0341 f(0) = 0 (absolute min) f(2) = 6.3496 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
83. 83. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = 1 f(−4/5) = 1.0341 f(0) = 0 (absolute min) f(2) = 6.3496 (absolute max) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
84. 84. Extreme values of an algebraic functionExampleFind the extreme values of f(x) = x2/3 (x + 2) on [−1, 2].SolutionWrite f(x) = x5/3 + 2x2/3 , then 5 2/3 4 −1/3 1 −1/3 f′ (x) = x + x = x (5x + 4) 3 3 3Thus f′ (−4/5) = 0 and f is not differentiable at 0. So our points tocheck are: f(−1) = 1 f(−4/5) = 1.0341 (relative max) f(0) = 0 (absolute min) f(2) = 6.3496 (absolute max) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 32 / 34
85. 85. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1]. V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
86. 86. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1].Solution xWe have f′ (x) = − √ , which is zero when x = 0. (f is not 4 − x2differentiable at ±2 as well.) V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
87. 87. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1].Solution xWe have f′ (x) = − √ , which is zero when x = 0. (f is not 4 − x2differentiable at ±2 as well.) So our points to check are: f(−2) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
88. 88. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1].Solution xWe have f′ (x) = − √ , which is zero when x = 0. (f is not 4 − x2differentiable at ±2 as well.) So our points to check are: f(−2) = 0 f(0) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
89. 89. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1].Solution xWe have f′ (x) = − √ , which is zero when x = 0. (f is not 4 − x2differentiable at ±2 as well.) So our points to check are: f(−2) = 0 f(0) = 2 f(1) = V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
90. 90. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1].Solution xWe have f′ (x) = − √ , which is zero when x = 0. (f is not 4 − x2differentiable at ±2 as well.) So our points to check are: f(−2) = 0 f(0) = 2 √ f(1) = 3 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
91. 91. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1].Solution xWe have f′ (x) = − √ , which is zero when x = 0. (f is not 4 − x2differentiable at ±2 as well.) So our points to check are: f(−2) = 0 (absolute min) f(0) = 2 √ f(1) = 3 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
92. 92. Extreme values of another algebraic functionExample √Find the extreme values of f(x) = 4 − x2 on [−2, 1].Solution xWe have f′ (x) = − √ , which is zero when x = 0. (f is not 4 − x2differentiable at ±2 as well.) So our points to check are: f(−2) = 0 (absolute min) f(0) = 2 (absolute max) √ f(1) = 3 V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 33 / 34
93. 93. Summary The Extreme Value Theorem: a continuous function on a closed interval must achieve its max and min Fermat’s Theorem: local extrema are critical points The Closed Interval Method: an algorithm for finding global extrema Show your work unless you want to end up like Fermat!V63.0121.041, Calculus I (NYU) Section 4.1 Maximum and Minimum Values November 8, 2010 34 / 34
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