SlideShare una empresa de Scribd logo
1 de 11
Descargar para leer sin conexión
V63.0121, Calculus I                                                        Section 4.7 : Antiderivatives   April 8, 2010



                                    Section 4.7                                                Notes

                                   Antiderivatives

                                  V63.0121.006/016, Calculus I

                                        New York University


                                          April 8, 2010


 Announcements

         Quiz April 16 on §§4.1–4.4
         Final Exam: Monday, May 10, 10:00am

Image credit: Ian Hampton




 Announcements
                                                                                               Notes




         Quiz April 16 on §§4.1–4.4
         Final Exam: Monday, May 10, 10:00am




     V63.0121, Calculus I (NYU)         Section 4.7 Antiderivatives   April 8, 2010   2 / 32




 Outline
                                                                                               Notes


 What is an antiderivative?

 Tabulating Antiderivatives
    Power functions
    Combinations
    Exponential functions
    Trigonometric functions

 Finding Antiderivatives Graphically

 Rectilinear motion



     V63.0121, Calculus I (NYU)         Section 4.7 Antiderivatives   April 8, 2010   3 / 32




                                                                                                                        1
V63.0121, Calculus I                                                          Section 4.7 : Antiderivatives   April 8, 2010


 Objectives
                                                                                                 Notes


        Given an expression for
        function f , find a
        differentiable function F
        such that F = f (F is called
        an antiderivative for f ).
        Given the graph of a
        function f , find a
        differentiable function F
        such that F = f
        Use antiderivatives to solve
        problems in rectilinear
        motion



    V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives        April 8, 2010   4 / 32




 Hard problem, easy check
                                                                                                 Notes
 Example
 Find an antiderivative for f (x) = ln x.

 Solution
 ???

 Example
 is F (x) = x ln x − x an antiderivative for f (x) = ln x?

 Solution

                      d
                      dx
                                                      1
                         (x ln x − x) = 1 · ln x + x · − 1 = ln x
                                                      x
                                                                    "

    V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives        April 8, 2010   5 / 32




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


 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) =⇒ f (y ) = f (x) + f (z)(y − x)
                    y −x

 But f (z) = 0, so f (y ) = f (x). Since this is true for all x and y in (a, b),
 then f is constant.


    V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives        April 8, 2010   6 / 32




                                                                                                                          2
V63.0121, Calculus I                                                                  Section 4.7 : Antiderivatives   April 8, 2010


 When two functions have the same derivative
                                                                                                         Notes

 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)




   V63.0121, Calculus I (NYU)      Section 4.7 Antiderivatives                  April 8, 2010   7 / 32




 Outline
                                                                                                         Notes


 What is an antiderivative?

 Tabulating Antiderivatives
    Power functions
    Combinations
    Exponential functions
    Trigonometric functions

 Finding Antiderivatives Graphically

 Rectilinear motion



   V63.0121, Calculus I (NYU)      Section 4.7 Antiderivatives                  April 8, 2010   8 / 32




 Antiderivatives of power functions
                                                                                                         Notes

                                                                 y f (x) = 2x
                                                                                f (x) = x 2
  Recall that the derivative of a
  power function is a power
  function.                                                                     F (x) = ?

  Fact (The Power Rule)
  If f (x) = x r , then f (x) = rx r −1 .

  So in looking for antiderivatives
  of power functions, try power                                                 x
  functions!




   V63.0121, Calculus I (NYU)      Section 4.7 Antiderivatives                  April 8, 2010   9 / 32




                                                                                                                                  3
V63.0121, Calculus I                                                                       Section 4.7 : Antiderivatives   April 8, 2010


 Example
                                                                                                              Notes
 Find an antiderivative for the function f (x) = x 3 .

 Solution

        Try a power function F (x) = ax r
        Then F (x) = arx r −1 , so we want arx r −1 = x 3 .
                                                       1
        r − 1 = 3 =⇒ r = 4, and ar = 1 =⇒ a = .
                                                       4
                  1 4
        So F (x) = x is an antiderivative.
                  4
        Check:
                            d 1 4
                           dx 4
                                   x
                                             1
                                       = 4 · x 4−1 = x 3
                                             4
                                                                               "
                                1
        Any others? Yes, F (x) = x 4 + C is the most general form.
                                4

   V63.0121, Calculus I (NYU)             Section 4.7 Antiderivatives               April 8, 2010   10 / 32




                                                                                                              Notes
 Fact (The Power Rule for antiderivatives)
 If f (x) = x r , then
                                            1 r +1
                                         F (x) =
                                               x
                                          r +1
 is an antiderivative for f . . . as long as r = −1.

 Fact
                         1
 If f (x) = x −1 =         , then
                         x
                                         F (x) = ln |x| + C

 is an antiderivative for f .




   V63.0121, Calculus I (NYU)             Section 4.7 Antiderivatives               April 8, 2010   11 / 32




 What’s with the absolute value?
                                                                                                              Notes
                                                       ln(x)            if x > 0;
                                F (x) = ln |x| =
                                                       ln(−x)           if x < 0.

        The domain of F is all nonzero numbers, while ln x is only defined on
        positive numbers.
        If x > 0,
                                      d
                                      dx
                                         ln |x| =
                                                  d
                                                  dx
                                                     ln(x) =
                                                             1
                                                             x
                                                                             "
        If x < 0,
                           d
                           dx
                              ln |x| =
                                       d
                                       dx
                                          ln(−x) =
                                                    1
                                                   −x
                                                      · (−1) =
                                                               1
                                                               x
                                                                                    "
        We prefer the antiderivative with the larger domain.
   V63.0121, Calculus I (NYU)             Section 4.7 Antiderivatives               April 8, 2010   12 / 32




                                                                                                                                       4
V63.0121, Calculus I                                                        Section 4.7 : Antiderivatives   April 8, 2010


 Graph of ln |x|
                                                                                               Notes
                                  y




                                                                 F (x) = ln(x) ln |x|

                                                                 f (x) = 1/x
                                                                 x




   V63.0121, Calculus I (NYU)      Section 4.7 Antiderivatives       April 8, 2010   13 / 32




 Combinations of antiderivatives
                                                                                               Notes
 Fact (Sum and Constant Multiple Rule for Antiderivatives)

      If F is an antiderivative of f and G is an antiderivative of g , then
      F + G is an antiderivative of f + g .
      If F is an antiderivative of f and c is a constant, then cF is an
      antiderivative of cf .

 Proof.
 These follow from the sum and constant multiple rule for derivatives:
      If F = f and G = g , then

                                (F + G ) = F + G = f + g

      Or, if F = f ,
                                      (cF ) = cF = cf

   V63.0121, Calculus I (NYU)      Section 4.7 Antiderivatives       April 8, 2010   14 / 32




 Antiderivatives of Polynomials
                                                                                               Notes
 Example
 Find an antiderivative for f (x) = 16x + 5.

 Solution
                 1
 The expression x 2 is an antiderivative for x, and x is an antiderivative for
                 2
 1. So
                           1 2
              F (x) = 16 ·   x + 5 · x + C = 8x 2 + 5x + C
                           2
 is the antiderivative of f .

 Question
 Why do we not need two C ’s?

 Answer
 A combination of two arbitrary constants is still an arbitrary constant.
   V63.0121, Calculus I (NYU)      Section 4.7 Antiderivatives       April 8, 2010   15 / 32




                                                                                                                        5
V63.0121, Calculus I                                                                 Section 4.7 : Antiderivatives   April 8, 2010


 Exponential Functions
                                                                                                        Notes
 Fact
 If f (x) = ax , f (x) = (ln a)ax .

 Accordingly,
 Fact
                                        1 x
 If f (x) = ax , then F (x) =               a + C is the antiderivative of f .
                                       ln a

 Proof.
 Check it yourself.

 In particular,
 Fact
 If f (x) = e x , then F (x) = e x + C is the antiderivative of f .

   V63.0121, Calculus I (NYU)            Section 4.7 Antiderivatives          April 8, 2010   16 / 32




 Logarithmic functions?
                                                                                                        Notes

        Remember we found
                                           F (x) = x ln x − x
        is an antiderivative of f (x) = ln x.
        This is not obvious. See Calc II for the full story.
                                                ln x
        However, using the fact that loga x =        , we get:
                                                ln a

 Fact
 If f (x) = loga (x)

                                 1                                  1
                F (x) =              (x ln x − x) + C = x loga x −      x +C
                                ln a                               ln a
 is the antiderivative of f (x).


   V63.0121, Calculus I (NYU)            Section 4.7 Antiderivatives          April 8, 2010   17 / 32




 Trigonometric functions
                                                                                                        Notes


 Fact

                           d                             d
                              sin x = cos x                 cos x = − sin x
                           dx                            dx

 So to turn these around,
 Fact

        The function F (x) = − cos x + C is the antiderivative of f (x) = sin x.
        The function F (x) = sin x + C is the antiderivative of f (x) = cos x.




   V63.0121, Calculus I (NYU)            Section 4.7 Antiderivatives          April 8, 2010   18 / 32




                                                                                                                                 6
V63.0121, Calculus I                                                                    Section 4.7 : Antiderivatives   April 8, 2010


 More Trig
                                                                                                           Notes
 Example
 Find an antiderivative of f (x) = tan x.

 Solution
 ???

 Answer
 F (x) = ln(sec x).

 Check

                d
                dx
                   =
                       1
                          ·
                            d
                     sec x dx
                              sec x =
                                        1
                                      sec x
                                            · sec x tan x = tan x                 "
 More about this later.
   V63.0121, Calculus I (NYU)           Section 4.7 Antiderivatives              April 8, 2010   19 / 32




 Outline
                                                                                                           Notes


 What is an antiderivative?

 Tabulating Antiderivatives
    Power functions
    Combinations
    Exponential functions
    Trigonometric functions

 Finding Antiderivatives Graphically

 Rectilinear motion



   V63.0121, Calculus I (NYU)           Section 4.7 Antiderivatives              April 8, 2010   20 / 32




 Problem
 Below is the graph of a function f . Draw the graph of an antiderivative for                              Notes
 F.

                  y




                                                                          y = f (x)


                                                                           x
                                1   2         3         4         5   6




   V63.0121, Calculus I (NYU)           Section 4.7 Antiderivatives              April 8, 2010   21 / 32




                                                                                                                                    7
V63.0121, Calculus I                                                                           Section 4.7 : Antiderivatives   April 8, 2010


 Using f to make a sign chart for F
                                                                                                                  Notes
 Assuming F = f , we can make a sign chart for f and f to find the
 intervals of monotonicity and concavity for for F :

                                                       +        +       −       −       +     f =F

      y                                           1        2       3  4          5          6F
                                                                  max           min

                                                       ++ −− −− ++ ++ f = F

             1 2 3 4 5 6
                                x                 1       2 3   4 5  6F
                                                         IP    IP

                                                   ?       ?        ?       ?       ?       ?F
                                       1    2    3    4   5                                 6 shape
 The only question left is: What are the function values?

   V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives                         April 8, 2010   22 / 32




 Could you repeat the question?
                                                                                                                  Notes
 Problem
 Below is the graph of a function f . Draw the graph of the antiderivative
 for F with F (1) = 0.

                                                            y
 Solution
                                                                                                f
       We start with F (1) = 0.
       Using the sign chart, we                                                                 x
                                                                    1 2 3 4 5 6
       draw arcs with the specified
       monotonicity and concavity
       It’s harder to tell if/when F                                                            F
       crosses the axis; more about                                 1 2 3 4 5 6 shape
                                                                        IP
                                                                        max
                                                                        IP
                                                                        min




       that later.


   V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives                         April 8, 2010   23 / 32




 Outline
                                                                                                                  Notes


 What is an antiderivative?

 Tabulating Antiderivatives
    Power functions
    Combinations
    Exponential functions
    Trigonometric functions

 Finding Antiderivatives Graphically

 Rectilinear motion



   V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives                         April 8, 2010   24 / 32




                                                                                                                                           8
V63.0121, Calculus I                                                           Section 4.7 : Antiderivatives   April 8, 2010


 Say what?
                                                                                                  Notes




      “Rectilinear motion” just means motion along a line.
      Often we are given information about the velocity or acceleration of a
      moving particle and we want to know the equations of motion.




   V63.0121, Calculus I (NYU)         Section 4.7 Antiderivatives       April 8, 2010   25 / 32




 Application: Dead Reckoning
                                                                                                  Notes




   V63.0121, Calculus I (NYU)         Section 4.7 Antiderivatives       April 8, 2010   26 / 32




 Problem
 Suppose a particle of mass m is acted upon by a constant force F . Find                          Notes
 the position function s(t), the velocity function v (t), and the acceleration
 function a(t).

 Solution

      By Newton’s Second Law (F = ma) a constant force induces a
                                             F
      constant acceleration. So a(t) = a = .
                                             m
      Since v (t) = a(t), v (t) must be an antiderivative of the constant
      function a. So
                              v (t) = at + C = at + v0
      where v0 is the initial velocity.
      Since s (t) = v (t), s(t) must be an antiderivative of v (t), meaning

                                  1                 1
                            s(t) = at 2 + v0 t + C = at 2 + v0 t + s0
                                  2                 2

   V63.0121, Calculus I (NYU)         Section 4.7 Antiderivatives       April 8, 2010   27 / 32




                                                                                                                           9
V63.0121, Calculus I                                                     Section 4.7 : Antiderivatives   April 8, 2010


 An earlier Hatsumon
                                                                                            Notes

 Example
 Drop a ball off the roof of the Silver Center. What is its velocity when it
 hits the ground?

 Solution
 Assume s0 = 100 m, and v0 = 0. Approximate a = g ≈ −10. Then

                          s(t) = 100 − 5t 2
                     √       √
 So s(t) = 0 when t = 20 = 2 5. Then

                                 v (t) = −10t,
                                  √          √
 so the velocity at impact is v (2 5) = −20 5 m/s.


   V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives   April 8, 2010   28 / 32




 Example
                                                                                            Notes
 The skid marks made by an automobile indicate that its brakes were fully
 applied for a distance of 160 ft before it came to a stop. Suppose that the
 car in question has a constant deceleration of 20 ft/s2 under the conditions
 of the skid. How fast was the car traveling when its brakes were first
 applied?

 Solution (Setup)

      While breaking, the car has acceleration a(t) = −20
      Measure time 0 and position 0 when the car starts braking. So
      s(0) = 0.
      The car stops at time some t1 , when v (t1 ) = 0.
      We know that when s(t1 ) = 160.
      We want to know v (0), or v0 .


   V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives   April 8, 2010   29 / 32




 Implementing the Solution
                                                                                            Notes
 In general,
                                           1
                         s(t) = s0 + v0 t + at 2
                                           2
 Since s0 = 0 and a = −20, we have

                                   s(t) = v0 t − 10t 2
                                   v (t) = v0 − 20t

 for all t. Plugging in t = t1 ,
                                                    2
                                   160 = v0 t1 − 10t1
                                      0 = v0 − 20t1

 We need to solve these two equations.


   V63.0121, Calculus I (NYU)       Section 4.7 Antiderivatives   April 8, 2010   30 / 32




                                                                                                                    10
V63.0121, Calculus I                                                                          Section 4.7 : Antiderivatives   April 8, 2010


 Solving
                                                                                                                Notes
 We have
                                         2
                            v0 t1 −   10t1   = 160            v0 − 20t1 = 0


      The second gives t1 = v0 /20, so substitute into the first:

                                             v0      v0            2
                                      v0 ·      − 10                   = 160
                                             20      20
      or
                                   2
                                  v0    10v02
                                     −        = 160
                                  20     400
                                      2     2
                                    2v0 − v0 = 160 · 40 = 6400


      So v0 = 80 ft/s ≈ 55 mi/hr

   V63.0121, Calculus I (NYU)            Section 4.7 Antiderivatives                  April 8, 2010   31 / 32




 What have we learned today?
                                                                                                                Notes




         Antiderivatives are a useful
         concept, especially in motion
                                                                       y
         We can graph an
         antiderivative from the                                                       f
         graph of a function
                                                                                      xF
         We can compute                                                    1 2 3 4 5 6
         antiderivatives, but not
         always
                                                                                          2
                                                                           f (x) = e −x
                                                                           f (x) = ???

   V63.0121, Calculus I (NYU)            Section 4.7 Antiderivatives                  April 8, 2010   32 / 32




                                                                                                                Notes




                                                                                                                                         11

Más contenido relacionado

La actualidad más candente

Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)Matthew Leingang
 
Lesson 14: Derivatives of Logarithmic and Exponential Functions
Lesson 14: Derivatives of Logarithmic and Exponential FunctionsLesson 14: Derivatives of Logarithmic and Exponential Functions
Lesson 14: Derivatives of Logarithmic and Exponential FunctionsMatthew Leingang
 
Introduction to FDA and linear models
 Introduction to FDA and linear models Introduction to FDA and linear models
Introduction to FDA and linear modelstuxette
 
Chapter 3 projection
Chapter 3 projectionChapter 3 projection
Chapter 3 projectionNBER
 
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)Matthew Leingang
 
Lesson 13: Related Rates Problems
Lesson 13: Related Rates ProblemsLesson 13: Related Rates Problems
Lesson 13: Related Rates ProblemsMatthew Leingang
 
Numerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodNumerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodAlexander Decker
 
Lesson 28: Integration by Subsitution
Lesson 28: Integration by SubsitutionLesson 28: Integration by Subsitution
Lesson 28: Integration by SubsitutionMatthew Leingang
 
Invariant test
Invariant testInvariant test
Invariant testgsangui
 
Tro07 sparse-solutions-talk
Tro07 sparse-solutions-talkTro07 sparse-solutions-talk
Tro07 sparse-solutions-talkmpbchina
 
Chapter 2 pertubation
Chapter 2 pertubationChapter 2 pertubation
Chapter 2 pertubationNBER
 
Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...
Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...
Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...dayuhuang
 
Cunningham slides-ch2
Cunningham slides-ch2Cunningham slides-ch2
Cunningham slides-ch2cunningjames
 
Lecture on solving1
Lecture on solving1Lecture on solving1
Lecture on solving1NBER
 

La actualidad más candente (16)

Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)Lesson 26: The Fundamental Theorem of Calculus (handout)
Lesson 26: The Fundamental Theorem of Calculus (handout)
 
Lesson 14: Derivatives of Logarithmic and Exponential Functions
Lesson 14: Derivatives of Logarithmic and Exponential FunctionsLesson 14: Derivatives of Logarithmic and Exponential Functions
Lesson 14: Derivatives of Logarithmic and Exponential Functions
 
Introduction to FDA and linear models
 Introduction to FDA and linear models Introduction to FDA and linear models
Introduction to FDA and linear models
 
Chapter 3 projection
Chapter 3 projectionChapter 3 projection
Chapter 3 projection
 
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
 
Lesson 13: Related Rates Problems
Lesson 13: Related Rates ProblemsLesson 13: Related Rates Problems
Lesson 13: Related Rates Problems
 
Numerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodNumerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis method
 
Lesson 28: Integration by Subsitution
Lesson 28: Integration by SubsitutionLesson 28: Integration by Subsitution
Lesson 28: Integration by Subsitution
 
Invariant test
Invariant testInvariant test
Invariant test
 
Tro07 sparse-solutions-talk
Tro07 sparse-solutions-talkTro07 sparse-solutions-talk
Tro07 sparse-solutions-talk
 
Chapter 2 pertubation
Chapter 2 pertubationChapter 2 pertubation
Chapter 2 pertubation
 
1. df tests
1. df tests1. df tests
1. df tests
 
Al24258261
Al24258261Al24258261
Al24258261
 
Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...
Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...
Feature Extraction for Universal Hypothesis Testing via Rank-Constrained Opti...
 
Cunningham slides-ch2
Cunningham slides-ch2Cunningham slides-ch2
Cunningham slides-ch2
 
Lecture on solving1
Lecture on solving1Lecture on solving1
Lecture on solving1
 

Similar a Lesson 21: Antiderivatives (notes)

Lesson 21: Antiderivatives (slides)
Lesson 21: Antiderivatives (slides)Lesson 21: Antiderivatives (slides)
Lesson 21: Antiderivatives (slides)Matthew Leingang
 
Lesson 23: Antiderivatives (Section 041 slides)
Lesson 23: Antiderivatives (Section 041 slides)Lesson 23: Antiderivatives (Section 041 slides)
Lesson 23: Antiderivatives (Section 041 slides)Mel Anthony Pepito
 
Lesson 23: Antiderivatives (Section 021 slides)
Lesson 23: Antiderivatives (Section 021 slides)Lesson 23: Antiderivatives (Section 021 slides)
Lesson 23: Antiderivatives (Section 021 slides)Mel Anthony Pepito
 
Lesson 23: Antiderivatives (Section 021 handout)
Lesson 23: Antiderivatives (Section 021 handout)Lesson 23: Antiderivatives (Section 021 handout)
Lesson 23: Antiderivatives (Section 021 handout)Matthew Leingang
 
Lesson 26: Integration by Substitution (slides)
Lesson 26: Integration by Substitution (slides)Lesson 26: Integration by Substitution (slides)
Lesson 26: Integration by Substitution (slides)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)Mel Anthony Pepito
 
Lesson 25: The Fundamental Theorem of Calculus
Lesson 25: The Fundamental Theorem of CalculusLesson 25: The Fundamental Theorem of Calculus
Lesson 25: The Fundamental Theorem of CalculusMatthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)Matthew Leingang
 
Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)Mel Anthony Pepito
 
Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)Mel Anthony Pepito
 
Bai giang Dao ham rieng
Bai giang Dao ham riengBai giang Dao ham rieng
Bai giang Dao ham riengNhan Nguyen
 
Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Mel Anthony Pepito
 
Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)Mel Anthony Pepito
 
Lesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slidesLesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slidesMel Anthony Pepito
 
Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)
Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)
Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)Matthew Leingang
 

Similar a Lesson 21: Antiderivatives (notes) (20)

Lesson 21: Antiderivatives (slides)
Lesson 21: Antiderivatives (slides)Lesson 21: Antiderivatives (slides)
Lesson 21: Antiderivatives (slides)
 
Lesson 23: Antiderivatives
Lesson 23: AntiderivativesLesson 23: Antiderivatives
Lesson 23: Antiderivatives
 
Lesson 23: Antiderivatives (Section 041 slides)
Lesson 23: Antiderivatives (Section 041 slides)Lesson 23: Antiderivatives (Section 041 slides)
Lesson 23: Antiderivatives (Section 041 slides)
 
Lesson 23: Antiderivatives (Section 021 slides)
Lesson 23: Antiderivatives (Section 021 slides)Lesson 23: Antiderivatives (Section 021 slides)
Lesson 23: Antiderivatives (Section 021 slides)
 
Lesson 23: Antiderivatives (Section 021 handout)
Lesson 23: Antiderivatives (Section 021 handout)Lesson 23: Antiderivatives (Section 021 handout)
Lesson 23: Antiderivatives (Section 021 handout)
 
Lesson 26: Integration by Substitution (slides)
Lesson 26: Integration by Substitution (slides)Lesson 26: Integration by Substitution (slides)
Lesson 26: Integration by Substitution (slides)
 
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 slides)
 
Lesson 25: The Fundamental Theorem of Calculus
Lesson 25: The Fundamental Theorem of CalculusLesson 25: The Fundamental Theorem of Calculus
Lesson 25: The Fundamental Theorem of Calculus
 
Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)
Lesson 26: The Fundamental Theorem of Calculus (Section 041 handout)
 
Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)
 
Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)Lesson 5: Continuity (Section 41 slides)
Lesson 5: Continuity (Section 41 slides)
 
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
 
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
Lesson 26: The Fundamental Theorem of Calculus (Section 021 slides)
 
Bai giang Dao ham rieng
Bai giang Dao ham riengBai giang Dao ham rieng
Bai giang Dao ham rieng
 
Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)Lesson 15: Exponential Growth and Decay (Section 041 slides)
Lesson 15: Exponential Growth and Decay (Section 041 slides)
 
Lesson 4: Continuity
Lesson 4: ContinuityLesson 4: Continuity
Lesson 4: Continuity
 
Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)Lesson 15: Exponential Growth and Decay (Section 021 slides)
Lesson 15: Exponential Growth and Decay (Section 021 slides)
 
Lesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slidesLesson15 -exponential_growth_and_decay_021_slides
Lesson15 -exponential_growth_and_decay_021_slides
 
Lesson 1: Functions
Lesson 1: FunctionsLesson 1: Functions
Lesson 1: Functions
 
Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)
Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)
Lesson 20: Derivatives and the Shape of Curves (Section 041 slides)
 

Más de Matthew Leingang

Streamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choiceStreamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choiceMatthew Leingang
 
Electronic Grading of Paper Assessments
Electronic Grading of Paper AssessmentsElectronic Grading of Paper Assessments
Electronic Grading of Paper AssessmentsMatthew Leingang
 
Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Matthew Leingang
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Matthew Leingang
 
Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)Matthew Leingang
 
Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)Matthew Leingang
 
Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)Matthew Leingang
 
Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)Matthew Leingang
 
Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)Matthew Leingang
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Matthew Leingang
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Matthew Leingang
 
Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)Matthew Leingang
 
Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)Matthew Leingang
 
Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)Matthew Leingang
 
Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)Matthew Leingang
 
Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)Matthew Leingang
 
Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)Matthew Leingang
 
Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)Matthew Leingang
 

Más de Matthew Leingang (20)

Making Lesson Plans
Making Lesson PlansMaking Lesson Plans
Making Lesson Plans
 
Streamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choiceStreamlining assessment, feedback, and archival with auto-multiple-choice
Streamlining assessment, feedback, and archival with auto-multiple-choice
 
Electronic Grading of Paper Assessments
Electronic Grading of Paper AssessmentsElectronic Grading of Paper Assessments
Electronic Grading of Paper Assessments
 
Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)Lesson 27: Integration by Substitution (slides)
Lesson 27: Integration by Substitution (slides)
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)
 
Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)Lesson 26: The Fundamental Theorem of Calculus (slides)
Lesson 26: The Fundamental Theorem of Calculus (slides)
 
Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)Lesson 27: Integration by Substitution (handout)
Lesson 27: Integration by Substitution (handout)
 
Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)Lesson 25: Evaluating Definite Integrals (slides)
Lesson 25: Evaluating Definite Integrals (slides)
 
Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)Lesson 25: Evaluating Definite Integrals (handout)
Lesson 25: Evaluating Definite Integrals (handout)
 
Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)Lesson 24: Areas and Distances, The Definite Integral (handout)
Lesson 24: Areas and Distances, The Definite Integral (handout)
 
Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)Lesson 24: Areas and Distances, The Definite Integral (slides)
Lesson 24: Areas and Distances, The Definite Integral (slides)
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)
 
Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)Lesson 23: Antiderivatives (slides)
Lesson 23: Antiderivatives (slides)
 
Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)Lesson 22: Optimization Problems (slides)
Lesson 22: Optimization Problems (slides)
 
Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)Lesson 22: Optimization Problems (handout)
Lesson 22: Optimization Problems (handout)
 
Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)Lesson 21: Curve Sketching (slides)
Lesson 21: Curve Sketching (slides)
 
Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)Lesson 21: Curve Sketching (handout)
Lesson 21: Curve Sketching (handout)
 
Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)Lesson 20: Derivatives and the Shapes of Curves (slides)
Lesson 20: Derivatives and the Shapes of Curves (slides)
 
Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)Lesson 20: Derivatives and the Shapes of Curves (handout)
Lesson 20: Derivatives and the Shapes of Curves (handout)
 
Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)Lesson 19: The Mean Value Theorem (slides)
Lesson 19: The Mean Value Theorem (slides)
 

Último

1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Celine George
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...EduSkills OECD
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxmanuelaromero2013
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfJayanti Pande
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13Steve Thomason
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3JemimahLaneBuaron
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)eniolaolutunde
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 

Último (20)

1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
Presentation by Andreas Schleicher Tackling the School Absenteeism Crisis 30 ...
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
How to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptxHow to Make a Pirate ship Primary Education.pptx
How to Make a Pirate ship Primary Education.pptx
 
Web & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdfWeb & Social Media Analytics Previous Year Question Paper.pdf
Web & Social Media Analytics Previous Year Question Paper.pdf
 
The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13The Most Excellent Way | 1 Corinthians 13
The Most Excellent Way | 1 Corinthians 13
 
Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3Q4-W6-Restating Informational Text Grade 3
Q4-W6-Restating Informational Text Grade 3
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 
Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)Software Engineering Methodologies (overview)
Software Engineering Methodologies (overview)
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 

Lesson 21: Antiderivatives (notes)

  • 1. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Section 4.7 Notes Antiderivatives V63.0121.006/016, Calculus I New York University April 8, 2010 Announcements Quiz April 16 on §§4.1–4.4 Final Exam: Monday, May 10, 10:00am Image credit: Ian Hampton Announcements Notes Quiz April 16 on §§4.1–4.4 Final Exam: Monday, May 10, 10:00am V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 2 / 32 Outline Notes What is an antiderivative? Tabulating Antiderivatives Power functions Combinations Exponential functions Trigonometric functions Finding Antiderivatives Graphically Rectilinear motion V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 3 / 32 1
  • 2. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Objectives Notes Given an expression for function f , find a differentiable function F such that F = f (F is called an antiderivative for f ). Given the graph of a function f , find a differentiable function F such that F = f Use antiderivatives to solve problems in rectilinear motion V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 4 / 32 Hard problem, easy check Notes Example Find an antiderivative for f (x) = ln x. Solution ??? Example is F (x) = x ln x − x an antiderivative for f (x) = ln x? Solution d dx 1 (x ln x − x) = 1 · ln x + x · − 1 = ln x x " V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 5 / 32 Why the MVT is the MITC Most Important Theorem In Calculus! Notes 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) =⇒ f (y ) = f (x) + f (z)(y − x) y −x But f (z) = 0, so f (y ) = f (x). Since this is true for all x and y in (a, b), then f is constant. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 6 / 32 2
  • 3. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 When two functions have the same derivative Notes 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) V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 7 / 32 Outline Notes What is an antiderivative? Tabulating Antiderivatives Power functions Combinations Exponential functions Trigonometric functions Finding Antiderivatives Graphically Rectilinear motion V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 8 / 32 Antiderivatives of power functions Notes y f (x) = 2x f (x) = x 2 Recall that the derivative of a power function is a power function. F (x) = ? Fact (The Power Rule) If f (x) = x r , then f (x) = rx r −1 . So in looking for antiderivatives of power functions, try power x functions! V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 9 / 32 3
  • 4. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Example Notes Find an antiderivative for the function f (x) = x 3 . Solution Try a power function F (x) = ax r Then F (x) = arx r −1 , so we want arx r −1 = x 3 . 1 r − 1 = 3 =⇒ r = 4, and ar = 1 =⇒ a = . 4 1 4 So F (x) = x is an antiderivative. 4 Check: d 1 4 dx 4 x 1 = 4 · x 4−1 = x 3 4 " 1 Any others? Yes, F (x) = x 4 + C is the most general form. 4 V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 10 / 32 Notes Fact (The Power Rule for antiderivatives) If f (x) = x r , then 1 r +1 F (x) = x r +1 is an antiderivative for f . . . as long as r = −1. Fact 1 If f (x) = x −1 = , then x F (x) = ln |x| + C is an antiderivative for f . V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 11 / 32 What’s with the absolute value? Notes ln(x) if x > 0; F (x) = ln |x| = ln(−x) if x < 0. The domain of F is all nonzero numbers, while ln x is only defined on positive numbers. If x > 0, d dx ln |x| = d dx ln(x) = 1 x " If x < 0, d dx ln |x| = d dx ln(−x) = 1 −x · (−1) = 1 x " We prefer the antiderivative with the larger domain. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 12 / 32 4
  • 5. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Graph of ln |x| Notes y F (x) = ln(x) ln |x| f (x) = 1/x x V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 13 / 32 Combinations of antiderivatives Notes Fact (Sum and Constant Multiple Rule for Antiderivatives) If F is an antiderivative of f and G is an antiderivative of g , then F + G is an antiderivative of f + g . If F is an antiderivative of f and c is a constant, then cF is an antiderivative of cf . Proof. These follow from the sum and constant multiple rule for derivatives: If F = f and G = g , then (F + G ) = F + G = f + g Or, if F = f , (cF ) = cF = cf V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 14 / 32 Antiderivatives of Polynomials Notes Example Find an antiderivative for f (x) = 16x + 5. Solution 1 The expression x 2 is an antiderivative for x, and x is an antiderivative for 2 1. So 1 2 F (x) = 16 · x + 5 · x + C = 8x 2 + 5x + C 2 is the antiderivative of f . Question Why do we not need two C ’s? Answer A combination of two arbitrary constants is still an arbitrary constant. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 15 / 32 5
  • 6. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Exponential Functions Notes Fact If f (x) = ax , f (x) = (ln a)ax . Accordingly, Fact 1 x If f (x) = ax , then F (x) = a + C is the antiderivative of f . ln a Proof. Check it yourself. In particular, Fact If f (x) = e x , then F (x) = e x + C is the antiderivative of f . V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 16 / 32 Logarithmic functions? Notes Remember we found F (x) = x ln x − x is an antiderivative of f (x) = ln x. This is not obvious. See Calc II for the full story. ln x However, using the fact that loga x = , we get: ln a Fact If f (x) = loga (x) 1 1 F (x) = (x ln x − x) + C = x loga x − x +C ln a ln a is the antiderivative of f (x). V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 17 / 32 Trigonometric functions Notes Fact d d sin x = cos x cos x = − sin x dx dx So to turn these around, Fact The function F (x) = − cos x + C is the antiderivative of f (x) = sin x. The function F (x) = sin x + C is the antiderivative of f (x) = cos x. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 18 / 32 6
  • 7. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 More Trig Notes Example Find an antiderivative of f (x) = tan x. Solution ??? Answer F (x) = ln(sec x). Check d dx = 1 · d sec x dx sec x = 1 sec x · sec x tan x = tan x " More about this later. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 19 / 32 Outline Notes What is an antiderivative? Tabulating Antiderivatives Power functions Combinations Exponential functions Trigonometric functions Finding Antiderivatives Graphically Rectilinear motion V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 20 / 32 Problem Below is the graph of a function f . Draw the graph of an antiderivative for Notes F. y y = f (x) x 1 2 3 4 5 6 V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 21 / 32 7
  • 8. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Using f to make a sign chart for F Notes Assuming F = f , we can make a sign chart for f and f to find the intervals of monotonicity and concavity for for F : + + − − + f =F y 1 2 3 4 5 6F max min ++ −− −− ++ ++ f = F 1 2 3 4 5 6 x 1 2 3 4 5 6F IP IP ? ? ? ? ? ?F 1 2 3 4 5 6 shape The only question left is: What are the function values? V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 22 / 32 Could you repeat the question? Notes Problem Below is the graph of a function f . Draw the graph of the antiderivative for F with F (1) = 0. y Solution f We start with F (1) = 0. Using the sign chart, we x 1 2 3 4 5 6 draw arcs with the specified monotonicity and concavity It’s harder to tell if/when F F crosses the axis; more about 1 2 3 4 5 6 shape IP max IP min that later. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 23 / 32 Outline Notes What is an antiderivative? Tabulating Antiderivatives Power functions Combinations Exponential functions Trigonometric functions Finding Antiderivatives Graphically Rectilinear motion V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 24 / 32 8
  • 9. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Say what? Notes “Rectilinear motion” just means motion along a line. Often we are given information about the velocity or acceleration of a moving particle and we want to know the equations of motion. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 25 / 32 Application: Dead Reckoning Notes V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 26 / 32 Problem Suppose a particle of mass m is acted upon by a constant force F . Find Notes the position function s(t), the velocity function v (t), and the acceleration function a(t). Solution By Newton’s Second Law (F = ma) a constant force induces a F constant acceleration. So a(t) = a = . m Since v (t) = a(t), v (t) must be an antiderivative of the constant function a. So v (t) = at + C = at + v0 where v0 is the initial velocity. Since s (t) = v (t), s(t) must be an antiderivative of v (t), meaning 1 1 s(t) = at 2 + v0 t + C = at 2 + v0 t + s0 2 2 V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 27 / 32 9
  • 10. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 An earlier Hatsumon Notes Example Drop a ball off the roof of the Silver Center. What is its velocity when it hits the ground? Solution Assume s0 = 100 m, and v0 = 0. Approximate a = g ≈ −10. Then s(t) = 100 − 5t 2 √ √ So s(t) = 0 when t = 20 = 2 5. Then v (t) = −10t, √ √ so the velocity at impact is v (2 5) = −20 5 m/s. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 28 / 32 Example Notes The skid marks made by an automobile indicate that its brakes were fully applied for a distance of 160 ft before it came to a stop. Suppose that the car in question has a constant deceleration of 20 ft/s2 under the conditions of the skid. How fast was the car traveling when its brakes were first applied? Solution (Setup) While breaking, the car has acceleration a(t) = −20 Measure time 0 and position 0 when the car starts braking. So s(0) = 0. The car stops at time some t1 , when v (t1 ) = 0. We know that when s(t1 ) = 160. We want to know v (0), or v0 . V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 29 / 32 Implementing the Solution Notes In general, 1 s(t) = s0 + v0 t + at 2 2 Since s0 = 0 and a = −20, we have s(t) = v0 t − 10t 2 v (t) = v0 − 20t for all t. Plugging in t = t1 , 2 160 = v0 t1 − 10t1 0 = v0 − 20t1 We need to solve these two equations. V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 30 / 32 10
  • 11. V63.0121, Calculus I Section 4.7 : Antiderivatives April 8, 2010 Solving Notes We have 2 v0 t1 − 10t1 = 160 v0 − 20t1 = 0 The second gives t1 = v0 /20, so substitute into the first: v0 v0 2 v0 · − 10 = 160 20 20 or 2 v0 10v02 − = 160 20 400 2 2 2v0 − v0 = 160 · 40 = 6400 So v0 = 80 ft/s ≈ 55 mi/hr V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 31 / 32 What have we learned today? Notes Antiderivatives are a useful concept, especially in motion y We can graph an antiderivative from the f graph of a function xF We can compute 1 2 3 4 5 6 antiderivatives, but not always 2 f (x) = e −x f (x) = ??? V63.0121, Calculus I (NYU) Section 4.7 Antiderivatives April 8, 2010 32 / 32 Notes 11