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Section	4.2
                             The	Mean	Value	Theorem

                                 V63.0121.027, Calculus	I



                                   November	10, 2009



       Announcements
               Quiz	this	week	on	§§3.1–3.5

       .
.
Image	credit: Jimmywayne22
                                                       .    .   .   .   .   .
Outline



  Review: The	Closed	Interval	Method


  Rolle’s	Theorem


  The	Mean	Value	Theorem
     Applications


  Why	the	MVT is	the	MITC




                                       .   .   .   .   .   .
Flowchart	for	placing	extrema
Thanks	to	Fermat
    Suppose 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

                                                .   .       .       .       .   .
The	Closed	Interval	Method



   This	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 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.




                                                  .    .    .    .    .      .
Outline



  Review: The	Closed	Interval	Method


  Rolle’s	Theorem


  The	Mean	Value	Theorem
     Applications


  Why	the	MVT is	the	MITC




                                       .   .   .   .   .   .
Heuristic	Motivation	for	Rolle’s	Theorem

        If	you	bike	up	a	hill, then	back	down, at	some	point	your
        elevation	was	stationary.




                                                            .

.
Image	credit: SpringSun
                                                    .   .       .   .   .   .
Mathematical	Statement	of	Rolle’s	Theorem




  Theorem	(Rolle’s	Theorem)
  Let f be	continuous	on [a, b]
  and	differentiable	on (a, b).
  Suppose f(a) = f(b). Then
  there	exists	a	point c in (a, b)
  such	that f′ (c) = 0.              .            .             .
                                                 a
                                                 .            b
                                                              .




                                         .   .        .   .     .   .
Mathematical	Statement	of	Rolle’s	Theorem



                                                          c
                                                          ..
  Theorem	(Rolle’s	Theorem)
  Let f be	continuous	on [a, b]
  and	differentiable	on (a, b).
  Suppose f(a) = f(b). Then
  there	exists	a	point c in (a, b)
  such	that f′ (c) = 0.              .            .                  .
                                                 a
                                                 .                 b
                                                                   .




                                         .   .        .        .     .   .
Proof	of	Rolle’s	Theorem
   Proof.
       By	the	Extreme	Value	Theorem f must	achieve	its	maximum
       value	at	a	point c in [a, b].




                                           .   .   .   .    .    .
Proof	of	Rolle’s	Theorem
   Proof.
       By	the	Extreme	Value	Theorem f must	achieve	its	maximum
       value	at	a	point c in [a, b].
       If c is	in (a, b), great: it’s	a	local	maximum	and	so	by
       Fermat’s	Theorem f′ (c) = 0.




                                                .    .    .       .   .   .
Proof	of	Rolle’s	Theorem
   Proof.
       By	the	Extreme	Value	Theorem f must	achieve	its	maximum
       value	at	a	point c in [a, b].
       If c is	in (a, b), great: it’s	a	local	maximum	and	so	by
       Fermat’s	Theorem f′ (c) = 0.
       On	the	other	hand, if c = a or c = b, try	with	the	minimum.
       The	minimum	of f on [a, b] must	be	achieved	at	a	point d in
       [a, b].




                                                .    .    .       .   .   .
Proof	of	Rolle’s	Theorem
   Proof.
       By	the	Extreme	Value	Theorem f must	achieve	its	maximum
       value	at	a	point c in [a, b].
       If c is	in (a, b), great: it’s	a	local	maximum	and	so	by
       Fermat’s	Theorem f′ (c) = 0.
       On	the	other	hand, if c = a or c = b, try	with	the	minimum.
       The	minimum	of f on [a, b] must	be	achieved	at	a	point d in
       [a, b].
       If d is	in (a, b), great: it’s	a	local	minimum	and	so	by
       Fermat’s	Theorem f′ (d) = 0. If	not, d = a or d = b.




                                                 .   .    .       .   .   .
Proof	of	Rolle’s	Theorem
   Proof.
       By	the	Extreme	Value	Theorem f must	achieve	its	maximum
       value	at	a	point c in [a, b].
       If c is	in (a, b), great: it’s	a	local	maximum	and	so	by
       Fermat’s	Theorem f′ (c) = 0.
       On	the	other	hand, if c = a or c = b, try	with	the	minimum.
       The	minimum	of f on [a, b] must	be	achieved	at	a	point d in
       [a, b].
       If d is	in (a, b), great: it’s	a	local	minimum	and	so	by
       Fermat’s	Theorem f′ (d) = 0. If	not, d = a or d = b.
       If	we	still	haven’t	found	a	point	in	the	interior, we	have	that
       the	maximum	and	minimum	values	of f on [a, b] occur	at
       both	endpoints.



                                                 .   .    .       .   .   .
Proof	of	Rolle’s	Theorem
   Proof.
       By	the	Extreme	Value	Theorem f must	achieve	its	maximum
       value	at	a	point c in [a, b].
       If c is	in (a, b), great: it’s	a	local	maximum	and	so	by
       Fermat’s	Theorem f′ (c) = 0.
       On	the	other	hand, if c = a or c = b, try	with	the	minimum.
       The	minimum	of f on [a, b] must	be	achieved	at	a	point d in
       [a, b].
       If d is	in (a, b), great: it’s	a	local	minimum	and	so	by
       Fermat’s	Theorem f′ (d) = 0. If	not, d = a or d = b.
       If	we	still	haven’t	found	a	point	in	the	interior, we	have	that
       the	maximum	and	minimum	values	of f on [a, b] occur	at
       both	endpoints. But	we	already	know	that f(a) = f(b).



                                                 .   .    .       .   .   .
Proof	of	Rolle’s	Theorem
   Proof.
       By	the	Extreme	Value	Theorem f must	achieve	its	maximum
       value	at	a	point c in [a, b].
       If c is	in (a, b), great: it’s	a	local	maximum	and	so	by
       Fermat’s	Theorem f′ (c) = 0.
       On	the	other	hand, if c = a or c = b, try	with	the	minimum.
       The	minimum	of f on [a, b] must	be	achieved	at	a	point d in
       [a, b].
       If d is	in (a, b), great: it’s	a	local	minimum	and	so	by
       Fermat’s	Theorem f′ (d) = 0. If	not, d = a or d = b.
       If	we	still	haven’t	found	a	point	in	the	interior, we	have	that
       the	maximum	and	minimum	values	of f on [a, b] occur	at
       both	endpoints. But	we	already	know	that f(a) = f(b). If
       these	are	the	maximum	and	minimum	values, f is constant
       on [a, b] and	any	point x in (a, b) will	have f′ (x) = 0.
                                                 .   .    .       .   .   .
Flowchart	proof	of	Rolle’s	Theorem

       .                       .                           .
         Let c be               Let d be                       endpoints
             .                      .                               .
                                                                are max
       the max pt              the min pt
                                                                and min



                                                           .
       .                       .                                 f is
            is c. an
                        y
                        . es        is d. an.   y
                                                . es               .
                                                               constant
           endpoint?               endpoint?
                                                               on [a, b]

               n
               .o                       n
                                        .o
                                                           .
       .                       .                               f′ (x) .≡ 0
   .       f (c) .= 0
           ′
                                   f (d) .= 0
                                    ′
                                                               on (a, b)

                                                   .   .       .     .       .   .
Outline



  Review: The	Closed	Interval	Method


  Rolle’s	Theorem


  The	Mean	Value	Theorem
     Applications


  Why	the	MVT is	the	MITC




                                       .   .   .   .   .   .
Heuristic	Motivation	for	The	Mean	Value	Theorem
        If	you	drive	between	points A and B, at	some	time	your
        speedometer	reading	was	the	same	as	your	average	speed	over
        the	drive.




                                                                  .
.
Image	credit: ClintJCL
                                                 .   .    .   .       .   .
The	Mean	Value	Theorem



 Theorem	(The	Mean	Value
 Theorem)
 Let f be	continuous	on [a, b]
 and	differentiable	on (a, b).
 Then	there	exists	a	point c in
 (a, b) such	that                                            .
                                                           b
                                                           .
      f(b) − f(a)                 .            .
                  = f′ (c).                   a
                                              .
         b−a




                                      .   .        .   .     .   .
The	Mean	Value	Theorem



 Theorem	(The	Mean	Value
 Theorem)
 Let f be	continuous	on [a, b]
 and	differentiable	on (a, b).
 Then	there	exists	a	point c in
 (a, b) such	that                                            .
                                                           b
                                                           .
      f(b) − f(a)                 .            .
                  = f′ (c).                   a
                                              .
         b−a




                                      .   .        .   .     .   .
The	Mean	Value	Theorem



 Theorem	(The	Mean	Value
 Theorem)                                              c
                                                       .
 Let f be	continuous	on [a, b]
 and	differentiable	on (a, b).
 Then	there	exists	a	point c in
 (a, b) such	that                                                .
                                                               b
                                                               .
      f(b) − f(a)                 .            .
                  = f′ (c).                   a
                                              .
         b−a




                                      .   .        .       .     .   .
Rolle	vs. MVT

                             f(b) − f(a)
          f′ (c) = 0                     = f′ (c)
                                b−a

                  c
                  ..                              c
                                                  ..




                                                             .
                                                           b
                                                           .
      .     .            .   .            .
           a
           .           b
                       .                 a
                                         .




                                 .   .        .        .     .   .
Rolle	vs. MVT

                                              f(b) − f(a)
           f′ (c) = 0                                     = f′ (c)
                                                 b−a

                   c
                   ..                                              c
                                                                   ..




                                                                              .
                                                                            b
                                                                            .
      .      .            .                   .            .
            a
            .           b
                        .                                 a
                                                          .

  If	the x-axis	is	skewed	the	pictures	look	the	same.


                                                  .   .        .        .     .   .
Proof	of	the	Mean	Value	Theorem
  Proof.
  The	line	connecting (a, f(a)) and (b, f(b)) has	equation

                                 f(b) − f(a)
                    y − f(a) =               (x − a)
                                    b−a




                                                .      .   .   .   .   .
Proof	of	the	Mean	Value	Theorem
  Proof.
  The	line	connecting (a, f(a)) and (b, f(b)) has	equation

                                 f(b) − f(a)
                    y − f(a) =               (x − a)
                                    b−a
  Apply	Rolle’s	Theorem	to	the	function

                                      f(b) − f(a)
               g(x) = f(x) − f(a) −               (x − a).
                                         b−a




                                                 .     .     .   .   .   .
Proof	of	the	Mean	Value	Theorem
  Proof.
  The	line	connecting (a, f(a)) and (b, f(b)) has	equation

                                  f(b) − f(a)
                     y − f(a) =               (x − a)
                                     b−a
  Apply	Rolle’s	Theorem	to	the	function

                                       f(b) − f(a)
                g(x) = f(x) − f(a) −               (x − a).
                                          b−a
  Then g is	continuous	on [a, b] and	differentiable	on (a, b) since f
  is.




                                                  .     .     .   .   .   .
Proof	of	the	Mean	Value	Theorem
  Proof.
  The	line	connecting (a, f(a)) and (b, f(b)) has	equation

                                  f(b) − f(a)
                     y − f(a) =               (x − a)
                                     b−a
  Apply	Rolle’s	Theorem	to	the	function

                                       f(b) − f(a)
                g(x) = f(x) − f(a) −               (x − a).
                                          b−a
  Then g is	continuous	on [a, b] and	differentiable	on (a, b) since f
  is. Also g(a) = 0 and g(b) = 0 (check	both)




                                                  .     .     .   .   .   .
Proof	of	the	Mean	Value	Theorem
  Proof.
  The	line	connecting (a, f(a)) and (b, f(b)) has	equation

                                  f(b) − f(a)
                     y − f(a) =               (x − a)
                                     b−a
  Apply	Rolle’s	Theorem	to	the	function

                                       f(b) − f(a)
                g(x) = f(x) − f(a) −               (x − a).
                                          b−a
  Then g is	continuous	on [a, b] and	differentiable	on (a, b) since f
  is. Also g(a) = 0 and g(b) = 0 (check	both) So	by	Rolle’s
  Theorem	there	exists	a	point c in (a, b) such	that

                                            f(b) − f(a)
                    0 = g′ (c) = f′ (c) −               .
                                               b−a

                                                    .       .   .   .   .   .
Using	the	MVT to	count	solutions

   Example
   Show	that	there	is	a	unique	solution	to	the	equation x3 − x = 100
   in	the	interval [4, 5].




                                              .    .   .    .   .      .
Using	the	MVT to	count	solutions

   Example
   Show	that	there	is	a	unique	solution	to	the	equation x3 − x = 100
   in	the	interval [4, 5].

   Solution
       By	the	Intermediate	Value	Theorem, the	function
       f(x) = x3 − x must	take	the	value 100 at	some	point	on c in
       (4, 5).




                                              .    .   .    .   .      .
Using	the	MVT to	count	solutions

   Example
   Show	that	there	is	a	unique	solution	to	the	equation x3 − x = 100
   in	the	interval [4, 5].

   Solution
       By	the	Intermediate	Value	Theorem, the	function
       f(x) = x3 − x must	take	the	value 100 at	some	point	on c in
       (4, 5).
       If	there	were	two	points c1 and c2 with f(c1 ) = f(c2 ) = 100,
       then	somewhere	between	them	would	be	a	point c3
       between	them	with f′ (c3 ) = 0.




                                               .    .    .   .    .     .
Using	the	MVT to	count	solutions

   Example
   Show	that	there	is	a	unique	solution	to	the	equation x3 − x = 100
   in	the	interval [4, 5].

   Solution
       By	the	Intermediate	Value	Theorem, the	function
       f(x) = x3 − x must	take	the	value 100 at	some	point	on c in
       (4, 5).
       If	there	were	two	points c1 and c2 with f(c1 ) = f(c2 ) = 100,
       then	somewhere	between	them	would	be	a	point c3
       between	them	with f′ (c3 ) = 0.
       However, f′ (x) = 3x2 − 1, which	is	positive	all	along (4, 5).
       So	this	is	impossible.


                                                .    .    .    .   .    .
Example
We	know	that |sin x| ≤ 1 for	all x. Show	that |sin x| ≤ |x|.




                                              .    .    .      .   .   .
Example
We	know	that |sin x| ≤ 1 for	all x. Show	that |sin x| ≤ |x|.

Solution
Apply	the	MVT to	the	function f(t) = sin t on [0, x]. We	get

                       sin x − sin 0
                                     = cos(c)
                           x−0
for	some c in (0, x). Since |cos(c)| ≤ 1, we	get

                    sin x
                          ≤ 1 =⇒ |sin x| ≤ |x|
                      x




                                                .   .   .      .   .   .
Example
Let f be	a	differentiable	function	with f(1) = 3 and f′ (x) < 2 for
all x in [0, 5]. Could f(4) ≥ 9?




                                               .   .    .    .    .   .
Example
 Let f be	a	differentiable	function	with f(1) = 3 and f′ (x) < 2 for
 all x in [0, 5]. Could f(4) ≥ 9?

 Solution                                                                 . 4, 9 )
                                                                          (
                                                      y
                                                      .                              .
By	MVT

       f(4) − f(1)                                                           . 4, f(4))
                                                                             (
                   = f′ (c) < 2                                                    .
          4−1
for	some c in (1, 4). Therefore
                                                    . 1, 3 )
                                                    (
                                                                  .
f(4) = f(1) + f′ (c)(3) < 3 + 2 · 3 = 9.

So	no, it	is	impossible	that f(4) ≥ 9.
                                                              .                              x
                                                                                             .


                                                .         .           .       .          .       .
Question
A driver	travels	along	the	New	Jersey	Turnpike	using	EZ-Pass. The
system	takes	note	of	the	time	and	place	the	driver	enters	and	exits
the	Turnpike. A week	after	his	trip, the	driver	gets	a	speeding
ticket	in	the	mail. Which	of	the	following	best	describes	the
situation?
(a) EZ-Pass	cannot	prove	that	the	driver	was	speeding
(b) EZ-Pass	can	prove	that	the	driver	was	speeding
(c) The	driver’s	actual	maximum	speed	exceeds	his	ticketed
    speed
(d) Both	(b)	and	(c).
Be	prepared	to	justify	your	answer.



                                             .   .    .    .   .      .
Question
A driver	travels	along	the	New	Jersey	Turnpike	using	EZ-Pass. The
system	takes	note	of	the	time	and	place	the	driver	enters	and	exits
the	Turnpike. A week	after	his	trip, the	driver	gets	a	speeding
ticket	in	the	mail. Which	of	the	following	best	describes	the
situation?
(a) EZ-Pass	cannot	prove	that	the	driver	was	speeding
(b) EZ-Pass	can	prove	that	the	driver	was	speeding
(c) The	driver’s	actual	maximum	speed	exceeds	his	ticketed
    speed
(d) Both	(b)	and	(c).
Be	prepared	to	justify	your	answer.



                                             .   .    .    .   .      .
Outline



  Review: The	Closed	Interval	Method


  Rolle’s	Theorem


  The	Mean	Value	Theorem
     Applications


  Why	the	MVT is	the	MITC




                                       .   .   .   .   .   .
Fact
If f is	constant	on (a, b), then f′ (x) = 0 on (a, b).




                                                 .       .   .   .   .   .
Fact
If f is	constant	on (a, b), then f′ (x) = 0 on (a, b).

       The	limit	of	difference	quotients	must	be 0
       The	tangent	line	to	a	line	is	that	line, and	a	constant
       function’s	graph	is	a	horizontal	line, which	has	slope 0.
       Implied	by	the	power	rule	since c = cx0




                                                 .       .   .   .   .   .
Fact
If f is	constant	on (a, b), then f′ (x) = 0 on (a, b).

       The	limit	of	difference	quotients	must	be 0
       The	tangent	line	to	a	line	is	that	line, and	a	constant
       function’s	graph	is	a	horizontal	line, which	has	slope 0.
       Implied	by	the	power	rule	since c = cx0

Question
If f′ (x) = 0 is f necessarily	a	constant	function?




                                                 .       .   .   .   .   .
Fact
If f is	constant	on (a, b), then f′ (x) = 0 on (a, b).

       The	limit	of	difference	quotients	must	be 0
       The	tangent	line	to	a	line	is	that	line, and	a	constant
       function’s	graph	is	a	horizontal	line, which	has	slope 0.
       Implied	by	the	power	rule	since c = cx0

Question
If f′ (x) = 0 is f necessarily	a	constant	function?

       It	seems	true
       But	so	far	no	theorem	(that	we	have	proven)	uses	information
       about	the	derivative	of	a	function	to	determine	information
       about	the	function	itself


                                                 .       .   .   .   .   .
Why	the	MVT is	the	MITC
Most	Important	Theorem	In	Calculus!



    Theorem
    Let f′ = 0 on	an	interval (a, b).




                                        .   .   .   .   .   .
Why	the	MVT is	the	MITC
Most	Important	Theorem	In	Calculus!



    Theorem
    Let f′ = 0 on	an	interval (a, b). Then f is	constant	on (a, b).




                                                   .    .    .    .   .   .
Why	the	MVT is	the	MITC
Most	Important	Theorem	In	Calculus!



    Theorem
    Let f′ = 0 on	an	interval (a, b). Then f is	constant	on (a, b).

    Proof.
    Pick	any	points x and y in (a, b) with x < y. Then f is	continuous
    on [x, y] and	differentiable	on (x, y). By	MVT there	exists	a	point
    z in (x, y) such	that

                             f(y) − f(x)
                                         = f′ (z) = 0.
                                y−x

    So f(y) = f(x). Since	this	is	true	for	all x and y in (a, b), then f is
    constant.


                                                     .    .    .    .    .    .
Theorem
Suppose f and g are	two	differentiable	functions	on (a, b) with
f′ = g′ . Then f and g differ	by	a	constant. That	is, there	exists	a
constant C such	that f(x) = g(x) + C.




                                                .    .    .    .       .   .
Theorem
Suppose f and g are	two	differentiable	functions	on (a, b) with
f′ = g′ . Then f and g differ	by	a	constant. That	is, there	exists	a
constant C such	that f(x) = g(x) + C.

Proof.
     Let h(x) = f(x) − g(x)
     Then h′ (x) = f′ (x) − g′ (x) = 0 on (a, b)
     So h(x) = C, a	constant
     This	means f(x) − g(x) = C on (a, b)




                                                   .   .   .   .       .   .
MVT and	differentiability

   Example
   Let                                {
                                       −x   if x ≤ 0
                               f(x) =
                                       x2   if x ≥ 0
   Is f differentiable	at 0?




                                                       .   .   .   .   .   .
MVT and	differentiability

   Example
   Let                                {
                                       −x   if x ≤ 0
                               f(x) =
                                       x2   if x ≥ 0
   Is f differentiable	at 0?

   Solution	(from	the	definition)
   We	have
                      f(x) − f(0)        −x
                  lim             = lim      = −1
                 x→0−    x−0       x→0− x
                      f(x) − f(0)        x2
                  lim             = lim+    = lim+ x = 0
                 x→0+    x−0       x→0 x      x→0

   Since	these	limits	disagree, f is	not	differentiable	at 0.
                                                       .   .    .   .   .   .
MVT and	differentiability

   Example
   Let                                {
                                       −x    if x ≤ 0
                               f(x) =
                                       x2    if x ≥ 0
   Is f differentiable	at 0?

   Solution	(Sort	of)
   If x < 0, then f′ (x) = −1. If x > 0, then f′ (x) = 2x. Since

                    lim f′ (x) = 0 and lim f′ (x) = −1,
                    x→0+                    x→0−

   the	limit lim f′ (x) does	not	exist	and	so f is	not	differentiable	at 0.
            x→0




                                                        .   .   .   .   .     .
This	solution	is	valid	but	less	direct.
We	seem	to	be	using	the	following	fact: If lim f′ (x) does	not
                                                 x→a
exist, then f is	not	differentiable	at a.
equivalently: If f is	differentiable	at a, then lim f′ (x) exists.
                                                 x→a
But	this	“fact”	is	not	true!




                                             .    .    .    .        .   .
Differentiable	with	discontinuous	derivative

   It	is	possible	for	a	function f to	be	differentiable	at a even	if
   lim f′ (x) does	not	exist.
   x→a

   Example {
                  x2 sin(1/x)   if x ̸= 0
   Let f′ (x) =                           . Then	when x ̸= 0,
                  0             if x = 0

   f′ (x) = 2x sin(1/x) + x2 cos(1/x)(−1/x2 ) = 2x sin(1/x) − cos(1/x),

   which	has	no	limit	at 0. However,

                  f(x) − f(0)       x2 sin(1/x)
     f′ (0) = lim             = lim             = lim x sin(1/x) = 0
              x→0    x−0        x→0       x       x→0

   So f′ (0) = 0. Hence f is	differentiable	for	all x, but f′ is	not
   continuous	at 0!

                                                    .    .      .   .   .   .
MVT to	the	rescue
  Lemma
  Suppose f is	continuous	on [a, b] and lim f′ (x) = m. Then
                                         x→a+

                               f(x) − f(a)
                        lim                = m.
                        x→a+      x−a




                                                  .   .   .   .   .   .
MVT to	the	rescue
  Lemma
  Suppose f is	continuous	on [a, b] and lim f′ (x) = m. Then
                                             x→a+

                                f(x) − f(a)
                          lim               = m.
                         x→a+      x−a


  Proof.
  Choose x near a and	greater	than a. Then

                           f(x) − f(a)
                                       = f ′ (c x )
                              x−a
  for	some cx where a < cx < x. As x → a, cx → a as	well, so:

                  f(x) − f(a)
            lim               = lim f′ (cx ) = lim f′ (x) = m.
           x→a+      x−a       x→a+           x→a+


                                                      .   .   .   .   .   .
Theorem
Suppose
                 lim f′ (x) = m1 and lim f′ (x) = m2
                x→a−                   x→a+

If m1 = m2 , then f is	differentiable	at a. If m1 ̸= m2 , then f is	not
differentiable	at a.




                                                 .    .    .    .    .    .
Theorem
Suppose
                 lim f′ (x) = m1 and lim f′ (x) = m2
                x→a−                   x→a+

If m1 = m2 , then f is	differentiable	at a. If m1 ̸= m2 , then f is	not
differentiable	at a.

Proof.
We	know	by	the	lemma	that

                         f(x) − f(a)
                       lim           = lim f′ (x)
                    x→a−    x−a       x→a−
                         f(x) − f(a)
                     lim             = lim f′ (x)
                    x→a+    x−a       x→a+

The	two-sided	limit	exists	if	(and	only	if)	the	two	right-hand	sides
agree.

                                                 .    .    .    .    .    .
What	have	we	learned	today?




      Rolle’s	Theorem: there	is	a	stationary	point
      Mean	Value	Theorem: at	some	point	the	instantaneous	rate
      of	change	equals	the	average	rate	of	change	(The	Most
      Important	Theorem	in	Calculus)
      Only	constant	functions	have	a	derivative	of	zero.




                                              .      .   .   .   .   .

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Lesson 20: The Mean Value Theorem

  • 1. Section 4.2 The Mean Value Theorem V63.0121.027, Calculus I November 10, 2009 Announcements Quiz this week on §§3.1–3.5 . . Image credit: Jimmywayne22 . . . . . .
  • 2. Outline Review: The Closed Interval Method Rolle’s Theorem The Mean Value Theorem Applications Why the MVT is the MITC . . . . . .
  • 3. Flowchart for placing extrema Thanks to Fermat Suppose 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 . . . . . .
  • 4. The Closed Interval Method This 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 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. . . . . . .
  • 5. Outline Review: The Closed Interval Method Rolle’s Theorem The Mean Value Theorem Applications Why the MVT is the MITC . . . . . .
  • 6. Heuristic Motivation for Rolle’s Theorem If you bike up a hill, then back down, at some point your elevation was stationary. . . Image credit: SpringSun . . . . . .
  • 7. Mathematical Statement of Rolle’s Theorem Theorem (Rolle’s Theorem) Let f be continuous on [a, b] and differentiable on (a, b). Suppose f(a) = f(b). Then there exists a point c in (a, b) such that f′ (c) = 0. . . . a . b . . . . . . .
  • 8. Mathematical Statement of Rolle’s Theorem c .. Theorem (Rolle’s Theorem) Let f be continuous on [a, b] and differentiable on (a, b). Suppose f(a) = f(b). Then there exists a point c in (a, b) such that f′ (c) = 0. . . . a . b . . . . . . .
  • 9. Proof of Rolle’s Theorem Proof. By the Extreme Value Theorem f must achieve its maximum value at a point c in [a, b]. . . . . . .
  • 10. Proof of Rolle’s Theorem Proof. By the Extreme Value Theorem f must achieve its maximum value at a point c in [a, b]. If c is in (a, b), great: it’s a local maximum and so by Fermat’s Theorem f′ (c) = 0. . . . . . .
  • 11. Proof of Rolle’s Theorem Proof. By the Extreme Value Theorem f must achieve its maximum value at a point c in [a, b]. If c is in (a, b), great: it’s a local maximum and so by Fermat’s Theorem f′ (c) = 0. On the other hand, if c = a or c = b, try with the minimum. The minimum of f on [a, b] must be achieved at a point d in [a, b]. . . . . . .
  • 12. Proof of Rolle’s Theorem Proof. By the Extreme Value Theorem f must achieve its maximum value at a point c in [a, b]. If c is in (a, b), great: it’s a local maximum and so by Fermat’s Theorem f′ (c) = 0. On the other hand, if c = a or c = b, try with the minimum. The minimum of f on [a, b] must be achieved at a point d in [a, b]. If d is in (a, b), great: it’s a local minimum and so by Fermat’s Theorem f′ (d) = 0. If not, d = a or d = b. . . . . . .
  • 13. Proof of Rolle’s Theorem Proof. By the Extreme Value Theorem f must achieve its maximum value at a point c in [a, b]. If c is in (a, b), great: it’s a local maximum and so by Fermat’s Theorem f′ (c) = 0. On the other hand, if c = a or c = b, try with the minimum. The minimum of f on [a, b] must be achieved at a point d in [a, b]. If d is in (a, b), great: it’s a local minimum and so by Fermat’s Theorem f′ (d) = 0. If not, d = a or d = b. If we still haven’t found a point in the interior, we have that the maximum and minimum values of f on [a, b] occur at both endpoints. . . . . . .
  • 14. Proof of Rolle’s Theorem Proof. By the Extreme Value Theorem f must achieve its maximum value at a point c in [a, b]. If c is in (a, b), great: it’s a local maximum and so by Fermat’s Theorem f′ (c) = 0. On the other hand, if c = a or c = b, try with the minimum. The minimum of f on [a, b] must be achieved at a point d in [a, b]. If d is in (a, b), great: it’s a local minimum and so by Fermat’s Theorem f′ (d) = 0. If not, d = a or d = b. If we still haven’t found a point in the interior, we have that the maximum and minimum values of f on [a, b] occur at both endpoints. But we already know that f(a) = f(b). . . . . . .
  • 15. Proof of Rolle’s Theorem Proof. By the Extreme Value Theorem f must achieve its maximum value at a point c in [a, b]. If c is in (a, b), great: it’s a local maximum and so by Fermat’s Theorem f′ (c) = 0. On the other hand, if c = a or c = b, try with the minimum. The minimum of f on [a, b] must be achieved at a point d in [a, b]. If d is in (a, b), great: it’s a local minimum and so by Fermat’s Theorem f′ (d) = 0. If not, d = a or d = b. If we still haven’t found a point in the interior, we have that the maximum and minimum values of f on [a, b] occur at both endpoints. But we already know that f(a) = f(b). If these are the maximum and minimum values, f is constant on [a, b] and any point x in (a, b) will have f′ (x) = 0. . . . . . .
  • 16. Flowchart proof of Rolle’s Theorem . . . Let c be Let d be endpoints . . . are max the max pt the min pt and min . . . f is is c. an y . es is d. an. y . es . constant endpoint? endpoint? on [a, b] n .o n .o . . . f′ (x) .≡ 0 . f (c) .= 0 ′ f (d) .= 0 ′ on (a, b) . . . . . .
  • 17. Outline Review: The Closed Interval Method Rolle’s Theorem The Mean Value Theorem Applications Why the MVT is the MITC . . . . . .
  • 18. Heuristic Motivation for The Mean Value Theorem If you drive between points A and B, at some time your speedometer reading was the same as your average speed over the drive. . . Image credit: ClintJCL . . . . . .
  • 19. The Mean Value Theorem Theorem (The Mean Value Theorem) Let f be continuous on [a, b] and differentiable on (a, b). Then there exists a point c in (a, b) such that . b . f(b) − f(a) . . = f′ (c). a . b−a . . . . . .
  • 20. The Mean Value Theorem Theorem (The Mean Value Theorem) Let f be continuous on [a, b] and differentiable on (a, b). Then there exists a point c in (a, b) such that . b . f(b) − f(a) . . = f′ (c). a . b−a . . . . . .
  • 21. The Mean Value Theorem Theorem (The Mean Value Theorem) c . Let f be continuous on [a, b] and differentiable on (a, b). Then there exists a point c in (a, b) such that . b . f(b) − f(a) . . = f′ (c). a . b−a . . . . . .
  • 22. Rolle vs. MVT f(b) − f(a) f′ (c) = 0 = f′ (c) b−a c .. c .. . b . . . . . . a . b . a . . . . . . .
  • 23. Rolle vs. MVT f(b) − f(a) f′ (c) = 0 = f′ (c) b−a c .. c .. . b . . . . . . a . b . a . If the x-axis is skewed the pictures look the same. . . . . . .
  • 24. Proof of the Mean Value Theorem Proof. The line connecting (a, f(a)) and (b, f(b)) has equation f(b) − f(a) y − f(a) = (x − a) b−a . . . . . .
  • 25. Proof of the Mean Value Theorem Proof. The line connecting (a, f(a)) and (b, f(b)) has equation f(b) − f(a) y − f(a) = (x − a) b−a Apply Rolle’s Theorem to the function f(b) − f(a) g(x) = f(x) − f(a) − (x − a). b−a . . . . . .
  • 26. Proof of the Mean Value Theorem Proof. The line connecting (a, f(a)) and (b, f(b)) has equation f(b) − f(a) y − f(a) = (x − a) b−a Apply Rolle’s Theorem to the function f(b) − f(a) g(x) = f(x) − f(a) − (x − a). b−a Then g is continuous on [a, b] and differentiable on (a, b) since f is. . . . . . .
  • 27. Proof of the Mean Value Theorem Proof. The line connecting (a, f(a)) and (b, f(b)) has equation f(b) − f(a) y − f(a) = (x − a) b−a Apply Rolle’s Theorem to the function f(b) − f(a) g(x) = f(x) − f(a) − (x − a). b−a Then g is continuous on [a, b] and differentiable on (a, b) since f is. Also g(a) = 0 and g(b) = 0 (check both) . . . . . .
  • 28. Proof of the Mean Value Theorem Proof. The line connecting (a, f(a)) and (b, f(b)) has equation f(b) − f(a) y − f(a) = (x − a) b−a Apply Rolle’s Theorem to the function f(b) − f(a) g(x) = f(x) − f(a) − (x − a). b−a Then g is continuous on [a, b] and differentiable on (a, b) since f is. Also g(a) = 0 and g(b) = 0 (check both) So by Rolle’s Theorem there exists a point c in (a, b) such that f(b) − f(a) 0 = g′ (c) = f′ (c) − . b−a . . . . . .
  • 29. Using the MVT to count solutions Example Show that there is a unique solution to the equation x3 − x = 100 in the interval [4, 5]. . . . . . .
  • 30. Using the MVT to count solutions Example Show that there is a unique solution to the equation x3 − x = 100 in the interval [4, 5]. Solution By the Intermediate Value Theorem, the function f(x) = x3 − x must take the value 100 at some point on c in (4, 5). . . . . . .
  • 31. Using the MVT to count solutions Example Show that there is a unique solution to the equation x3 − x = 100 in the interval [4, 5]. Solution By the Intermediate Value Theorem, the function f(x) = x3 − x must take the value 100 at some point on c in (4, 5). If there were two points c1 and c2 with f(c1 ) = f(c2 ) = 100, then somewhere between them would be a point c3 between them with f′ (c3 ) = 0. . . . . . .
  • 32. Using the MVT to count solutions Example Show that there is a unique solution to the equation x3 − x = 100 in the interval [4, 5]. Solution By the Intermediate Value Theorem, the function f(x) = x3 − x must take the value 100 at some point on c in (4, 5). If there were two points c1 and c2 with f(c1 ) = f(c2 ) = 100, then somewhere between them would be a point c3 between them with f′ (c3 ) = 0. However, f′ (x) = 3x2 − 1, which is positive all along (4, 5). So this is impossible. . . . . . .
  • 33. Example We know that |sin x| ≤ 1 for all x. Show that |sin x| ≤ |x|. . . . . . .
  • 34. Example We know that |sin x| ≤ 1 for all x. Show that |sin x| ≤ |x|. Solution Apply the MVT to the function f(t) = sin t on [0, x]. We get sin x − sin 0 = cos(c) x−0 for some c in (0, x). Since |cos(c)| ≤ 1, we get sin x ≤ 1 =⇒ |sin x| ≤ |x| x . . . . . .
  • 35. Example Let f be a differentiable function with f(1) = 3 and f′ (x) < 2 for all x in [0, 5]. Could f(4) ≥ 9? . . . . . .
  • 36. Example Let f be a differentiable function with f(1) = 3 and f′ (x) < 2 for all x in [0, 5]. Could f(4) ≥ 9? Solution . 4, 9 ) ( y . . By MVT f(4) − f(1) . 4, f(4)) ( = f′ (c) < 2 . 4−1 for some c in (1, 4). Therefore . 1, 3 ) ( . f(4) = f(1) + f′ (c)(3) < 3 + 2 · 3 = 9. So no, it is impossible that f(4) ≥ 9. . x . . . . . . .
  • 37. Question A driver travels along the New Jersey Turnpike using EZ-Pass. The system takes note of the time and place the driver enters and exits the Turnpike. A week after his trip, the driver gets a speeding ticket in the mail. Which of the following best describes the situation? (a) EZ-Pass cannot prove that the driver was speeding (b) EZ-Pass can prove that the driver was speeding (c) The driver’s actual maximum speed exceeds his ticketed speed (d) Both (b) and (c). Be prepared to justify your answer. . . . . . .
  • 38. Question A driver travels along the New Jersey Turnpike using EZ-Pass. The system takes note of the time and place the driver enters and exits the Turnpike. A week after his trip, the driver gets a speeding ticket in the mail. Which of the following best describes the situation? (a) EZ-Pass cannot prove that the driver was speeding (b) EZ-Pass can prove that the driver was speeding (c) The driver’s actual maximum speed exceeds his ticketed speed (d) Both (b) and (c). Be prepared to justify your answer. . . . . . .
  • 39. Outline Review: The Closed Interval Method Rolle’s Theorem The Mean Value Theorem Applications Why the MVT is the MITC . . . . . .
  • 40. Fact If f is constant on (a, b), then f′ (x) = 0 on (a, b). . . . . . .
  • 41. Fact If f is constant on (a, b), then f′ (x) = 0 on (a, b). The limit of difference quotients must be 0 The tangent line to a line is that line, and a constant function’s graph is a horizontal line, which has slope 0. Implied by the power rule since c = cx0 . . . . . .
  • 42. Fact If f is constant on (a, b), then f′ (x) = 0 on (a, b). The limit of difference quotients must be 0 The tangent line to a line is that line, and a constant function’s graph is a horizontal line, which has slope 0. Implied by the power rule since c = cx0 Question If f′ (x) = 0 is f necessarily a constant function? . . . . . .
  • 43. Fact If f is constant on (a, b), then f′ (x) = 0 on (a, b). The limit of difference quotients must be 0 The tangent line to a line is that line, and a constant function’s graph is a horizontal line, which has slope 0. Implied by the power rule since c = cx0 Question If f′ (x) = 0 is f necessarily a constant function? It seems true But so far no theorem (that we have proven) uses information about the derivative of a function to determine information about the function itself . . . . . .
  • 44. Why the MVT is the MITC Most Important Theorem In Calculus! Theorem Let f′ = 0 on an interval (a, b). . . . . . .
  • 45. Why the MVT is the MITC Most Important Theorem In Calculus! Theorem Let f′ = 0 on an interval (a, b). Then f is constant on (a, b). . . . . . .
  • 46. Why the MVT is the MITC Most Important Theorem In Calculus! Theorem Let f′ = 0 on an interval (a, b). Then f is constant on (a, b). Proof. Pick any points x and y in (a, b) with x < y. Then f is continuous on [x, y] and differentiable on (x, y). By MVT there exists a point z in (x, y) such that f(y) − f(x) = f′ (z) = 0. y−x So f(y) = f(x). Since this is true for all x and y in (a, b), then f is constant. . . . . . .
  • 47. Theorem Suppose f and g are two differentiable functions on (a, b) with f′ = g′ . Then f and g differ by a constant. That is, there exists a constant C such that f(x) = g(x) + C. . . . . . .
  • 48. Theorem Suppose f and g are two differentiable functions on (a, b) with f′ = g′ . Then f and g differ by a constant. That is, there exists a constant C such that f(x) = g(x) + C. Proof. Let h(x) = f(x) − g(x) Then h′ (x) = f′ (x) − g′ (x) = 0 on (a, b) So h(x) = C, a constant This means f(x) − g(x) = C on (a, b) . . . . . .
  • 49. MVT and differentiability Example Let { −x if x ≤ 0 f(x) = x2 if x ≥ 0 Is f differentiable at 0? . . . . . .
  • 50. MVT and differentiability Example Let { −x if x ≤ 0 f(x) = x2 if x ≥ 0 Is f differentiable at 0? Solution (from the definition) We have f(x) − f(0) −x lim = lim = −1 x→0− x−0 x→0− x f(x) − f(0) x2 lim = lim+ = lim+ x = 0 x→0+ x−0 x→0 x x→0 Since these limits disagree, f is not differentiable at 0. . . . . . .
  • 51. MVT and differentiability Example Let { −x if x ≤ 0 f(x) = x2 if x ≥ 0 Is f differentiable at 0? Solution (Sort of) If x < 0, then f′ (x) = −1. If x > 0, then f′ (x) = 2x. Since lim f′ (x) = 0 and lim f′ (x) = −1, x→0+ x→0− the limit lim f′ (x) does not exist and so f is not differentiable at 0. x→0 . . . . . .
  • 52. This solution is valid but less direct. We seem to be using the following fact: If lim f′ (x) does not x→a exist, then f is not differentiable at a. equivalently: If f is differentiable at a, then lim f′ (x) exists. x→a But this “fact” is not true! . . . . . .
  • 53. Differentiable with discontinuous derivative It is possible for a function f to be differentiable at a even if lim f′ (x) does not exist. x→a Example { x2 sin(1/x) if x ̸= 0 Let f′ (x) = . Then when x ̸= 0, 0 if x = 0 f′ (x) = 2x sin(1/x) + x2 cos(1/x)(−1/x2 ) = 2x sin(1/x) − cos(1/x), which has no limit at 0. However, f(x) − f(0) x2 sin(1/x) f′ (0) = lim = lim = lim x sin(1/x) = 0 x→0 x−0 x→0 x x→0 So f′ (0) = 0. Hence f is differentiable for all x, but f′ is not continuous at 0! . . . . . .
  • 54. MVT to the rescue Lemma Suppose f is continuous on [a, b] and lim f′ (x) = m. Then x→a+ f(x) − f(a) lim = m. x→a+ x−a . . . . . .
  • 55. MVT to the rescue Lemma Suppose f is continuous on [a, b] and lim f′ (x) = m. Then x→a+ f(x) − f(a) lim = m. x→a+ x−a Proof. Choose x near a and greater than a. Then f(x) − f(a) = f ′ (c x ) x−a for some cx where a < cx < x. As x → a, cx → a as well, so: f(x) − f(a) lim = lim f′ (cx ) = lim f′ (x) = m. x→a+ x−a x→a+ x→a+ . . . . . .
  • 56. Theorem Suppose lim f′ (x) = m1 and lim f′ (x) = m2 x→a− x→a+ If m1 = m2 , then f is differentiable at a. If m1 ̸= m2 , then f is not differentiable at a. . . . . . .
  • 57. Theorem Suppose lim f′ (x) = m1 and lim f′ (x) = m2 x→a− x→a+ If m1 = m2 , then f is differentiable at a. If m1 ̸= m2 , then f is not differentiable at a. Proof. We know by the lemma that f(x) − f(a) lim = lim f′ (x) x→a− x−a x→a− f(x) − f(a) lim = lim f′ (x) x→a+ x−a x→a+ The two-sided limit exists if (and only if) the two right-hand sides agree. . . . . . .
  • 58. What have we learned today? Rolle’s Theorem: there is a stationary point Mean Value Theorem: at some point the instantaneous rate of change equals the average rate of change (The Most Important Theorem in Calculus) Only constant functions have a derivative of zero. . . . . . .