SlideShare une entreprise Scribd logo
1  sur  35
11.11 Applications of
    Taylor Series
           −
Evaluate       correct to within an error
of 0.01.
11.11 Applications of
    Taylor Series
                −
Evaluate                    correct to within an error
of 0.01.

 −         ∞        (− )             ∞
     =      =          !    =         =   (− )   !

     =     −    !   +   !   −   !   + ···
11.11 Applications of
    Taylor Series
                  −
Evaluate                        correct to within an error
of 0.01.

 −           ∞        (− )               ∞
         =    =          !      =         =   (− )       !

         =   −    !   +    !    −   !   + ···
     −
             = −          · !   +   · !   −     · !   + ··· +
−           ∞        (− )               ∞
        =    =          !      =         =   (− )       !

        =   −    !   +    !    −   !   + ···
    −
            = −          · !   +   · !   −     · !   + ··· +
−           ∞        (− )                 ∞
        =    =          !        =         =   (− )         !

        =   −    !   +    !    −     !   + ···
    −
            = −          · !   +     · !   −       · !   + ··· +

    −
            =        −     · !   +       · !   −    · !   + ···
−           ∞        (− )                 ∞
        =    =          !        =         =   (− )         !

        =   −    !   +    !    −     !   + ···
    −
            = −          · !   +     · !   −       · !   + ··· +

    −
            =        −     · !   +       · !   −    · !   + ···

            =        −    +          −         +           − ···
−           ∞        (− )                 ∞
        =    =          !        =         =   (− )         !

        =   −    !   +    !    −     !   + ···
    −
            = −          · !   +     · !   −       · !   + ··· +

    −
            =        −     · !   +       · !   −    · !   + ···

            =        −    +          −         +           − ···

            ≈ .
What is the maximum error possible in using
the approximation

                 ≈ −      !   +   !
when   − . ≤   ≤ .    ?


For what value of      is this approximation
accurate to within   .         ?


What is the smallest degree of the Taylor
polynomial we can use to approximate if we
want the error in [  . , . ] to be less
than       ?
What is the maximum error possible in using
the approximation

                ≈ −      !   +   !
when   − . ≤   ≤ .   ?
What is the maximum error possible in using
the approximation

                  ≈ −       !   +     !
when   − . ≤     ≤ .    ?

Taylor’s Inequality:

             |   ( )|           | |
                            !
What is the maximum error possible in using
the approximation

                        ≈ −      !   +     !
when       − . ≤      ≤ .    ?

Taylor’s Inequality:

                  |   ( )|           | |
                               !
           ( )
       |         |=|−        |≤ ,              =
What is the maximum error possible in using
the approximation

                        ≈ −      !   +     !
when       − . ≤      ≤ .    ?

Taylor’s Inequality:

                  |   ( )|           | |
                               !
           ( )
       |         |=|−        |≤ ,              =
when       − . ≤      ≤ .
What is the maximum error possible in using
the approximation

                        ≈ −             !   +     !
when       − . ≤      ≤ .       ?

Taylor’s Inequality:

                  |   ( )|                  | |
                                  !
           ( )
       |         |=|−           |≤ ,                  =
when       − . ≤      ≤ .
                        .
                                    .
                            !
For what value of        is this approximation
accurate to within   .           ?
For what value of        is this approximation
accurate to within   .           ?

We want
             | |
                  < .
                !
For what value of        is this approximation
accurate to within   .           ?

We want
             | |
                  < .
                !
       | | < .            · !    .
For what value of        is this approximation
accurate to within   .           ?

We want
             | |
                  < .
                !
       | | < .            · !    .

                 | |< .
What is the smallest degree of the Taylor
polynomial we can use to approximate if we want
the error in [ . , . ] to be less than    ?
What is the smallest degree of the Taylor
polynomial we can use to approximate if we want
the error in [ . , . ] to be less than    ?

                      .
 |   ( )|       | |           .
            !             !
What is the smallest degree of the Taylor
polynomial we can use to approximate if we want
the error in [ . , . ] to be less than    ?

                      .
 |   ( )|       | |           .
            !             !
                      .
 |   ( )|       | |           .
            !             !
What is the smallest degree of the Taylor
polynomial we can use to approximate if we want
the error in [ . , . ] to be less than    ?

                       .
 |    ( )|       | |           .
             !             !
                       .
 |    ( )|       | |           .
             !             !
                       .
  |   ( )|       | |           .
             !             !
What is the smallest degree of the Taylor
polynomial we can use to approximate if we want
the error in [ . , . ] to be less than    ?

                       .
  |   ( )|       | |           .
             !             !
                       .
  |   ( )|       | |           .
             !             !
                       .
  |   ( )|       | |           .
             !             !
So we need the Taylor polynomial of degree 8.
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !
Taylor approximation of             .

                         +
     =       (   )              =           +           + ···
         =
                     (   + )!           !       !   !

Contenu connexe

En vedette

Taylor and maclaurian series
Taylor and maclaurian seriesTaylor and maclaurian series
Taylor and maclaurian seriesNishant Patel
 
Taylor Polynomials and Series
Taylor Polynomials and SeriesTaylor Polynomials and Series
Taylor Polynomials and SeriesMatthew Leingang
 
Taylor series and maclaurin with exercices
Taylor series and maclaurin with exercicesTaylor series and maclaurin with exercices
Taylor series and maclaurin with exercicesHernanFula
 
Calculus II - 35
Calculus II - 35Calculus II - 35
Calculus II - 35David Mao
 
Calculus II - 33
Calculus II - 33Calculus II - 33
Calculus II - 33David Mao
 
Calculus II - 20
Calculus II - 20Calculus II - 20
Calculus II - 20David Mao
 
Calculus II - 31
Calculus II - 31Calculus II - 31
Calculus II - 31David Mao
 
Calculus II - 36
Calculus II - 36Calculus II - 36
Calculus II - 36David Mao
 
Calculus II - 19
Calculus II - 19Calculus II - 19
Calculus II - 19David Mao
 
Caculus II - 37
Caculus II - 37Caculus II - 37
Caculus II - 37David Mao
 
Calculus II - 32
Calculus II - 32Calculus II - 32
Calculus II - 32David Mao
 
Calculus II - 25
Calculus II - 25Calculus II - 25
Calculus II - 25David Mao
 
Calculus II - 34
Calculus II - 34Calculus II - 34
Calculus II - 34David Mao
 
Calculus II - 29
Calculus II - 29Calculus II - 29
Calculus II - 29David Mao
 
Calculus II - 28
Calculus II - 28Calculus II - 28
Calculus II - 28David Mao
 
Calculus II - 18
Calculus II - 18Calculus II - 18
Calculus II - 18David Mao
 
Calculus II - 23
Calculus II - 23Calculus II - 23
Calculus II - 23David Mao
 

En vedette (20)

Taylor and maclaurian series
Taylor and maclaurian seriesTaylor and maclaurian series
Taylor and maclaurian series
 
Taylor series
Taylor seriesTaylor series
Taylor series
 
Taylor’s series
Taylor’s   seriesTaylor’s   series
Taylor’s series
 
Taylor Polynomials and Series
Taylor Polynomials and SeriesTaylor Polynomials and Series
Taylor Polynomials and Series
 
Taylor series and maclaurin with exercices
Taylor series and maclaurin with exercicesTaylor series and maclaurin with exercices
Taylor series and maclaurin with exercices
 
MEAN VALUE THEOREM
MEAN VALUE THEOREMMEAN VALUE THEOREM
MEAN VALUE THEOREM
 
Calculus II - 35
Calculus II - 35Calculus II - 35
Calculus II - 35
 
Calculus II - 33
Calculus II - 33Calculus II - 33
Calculus II - 33
 
Calculus II - 20
Calculus II - 20Calculus II - 20
Calculus II - 20
 
Calculus II - 31
Calculus II - 31Calculus II - 31
Calculus II - 31
 
Calculus II - 36
Calculus II - 36Calculus II - 36
Calculus II - 36
 
Calculus II - 19
Calculus II - 19Calculus II - 19
Calculus II - 19
 
Caculus II - 37
Caculus II - 37Caculus II - 37
Caculus II - 37
 
Calculus II - 32
Calculus II - 32Calculus II - 32
Calculus II - 32
 
Calculus II - 25
Calculus II - 25Calculus II - 25
Calculus II - 25
 
Calculus II - 34
Calculus II - 34Calculus II - 34
Calculus II - 34
 
Calculus II - 29
Calculus II - 29Calculus II - 29
Calculus II - 29
 
Calculus II - 28
Calculus II - 28Calculus II - 28
Calculus II - 28
 
Calculus II - 18
Calculus II - 18Calculus II - 18
Calculus II - 18
 
Calculus II - 23
Calculus II - 23Calculus II - 23
Calculus II - 23
 

Plus de David Mao

Calculus II - 27
Calculus II - 27Calculus II - 27
Calculus II - 27David Mao
 
Calculus II - 26
Calculus II - 26Calculus II - 26
Calculus II - 26David Mao
 
Calculus II - 24
Calculus II - 24Calculus II - 24
Calculus II - 24David Mao
 
Calculus II - 22
Calculus II - 22Calculus II - 22
Calculus II - 22David Mao
 
Calculus II - 21
Calculus II - 21Calculus II - 21
Calculus II - 21David Mao
 
Calculus II - 17
Calculus II - 17Calculus II - 17
Calculus II - 17David Mao
 
Calculus II - 16
Calculus II - 16Calculus II - 16
Calculus II - 16David Mao
 
Calculus II - 15
Calculus II - 15Calculus II - 15
Calculus II - 15David Mao
 
Calculus II - 14
Calculus II - 14Calculus II - 14
Calculus II - 14David Mao
 
Calculus II - 13
Calculus II - 13Calculus II - 13
Calculus II - 13David Mao
 
Calculus II - 12
Calculus II - 12Calculus II - 12
Calculus II - 12David Mao
 
Calculus II - 11
Calculus II - 11Calculus II - 11
Calculus II - 11David Mao
 
Calculus II - 10
Calculus II - 10Calculus II - 10
Calculus II - 10David Mao
 
Calculus II - 9
Calculus II - 9Calculus II - 9
Calculus II - 9David Mao
 
Calculus II - 8
Calculus II - 8Calculus II - 8
Calculus II - 8David Mao
 
Calculus II - 7
Calculus II - 7Calculus II - 7
Calculus II - 7David Mao
 

Plus de David Mao (16)

Calculus II - 27
Calculus II - 27Calculus II - 27
Calculus II - 27
 
Calculus II - 26
Calculus II - 26Calculus II - 26
Calculus II - 26
 
Calculus II - 24
Calculus II - 24Calculus II - 24
Calculus II - 24
 
Calculus II - 22
Calculus II - 22Calculus II - 22
Calculus II - 22
 
Calculus II - 21
Calculus II - 21Calculus II - 21
Calculus II - 21
 
Calculus II - 17
Calculus II - 17Calculus II - 17
Calculus II - 17
 
Calculus II - 16
Calculus II - 16Calculus II - 16
Calculus II - 16
 
Calculus II - 15
Calculus II - 15Calculus II - 15
Calculus II - 15
 
Calculus II - 14
Calculus II - 14Calculus II - 14
Calculus II - 14
 
Calculus II - 13
Calculus II - 13Calculus II - 13
Calculus II - 13
 
Calculus II - 12
Calculus II - 12Calculus II - 12
Calculus II - 12
 
Calculus II - 11
Calculus II - 11Calculus II - 11
Calculus II - 11
 
Calculus II - 10
Calculus II - 10Calculus II - 10
Calculus II - 10
 
Calculus II - 9
Calculus II - 9Calculus II - 9
Calculus II - 9
 
Calculus II - 8
Calculus II - 8Calculus II - 8
Calculus II - 8
 
Calculus II - 7
Calculus II - 7Calculus II - 7
Calculus II - 7
 

Dernier

#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptxLBM Solutions
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...HostedbyConfluent
 

Dernier (20)

#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptx
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
 

Calculus II - 30

  • 1. 11.11 Applications of Taylor Series − Evaluate correct to within an error of 0.01.
  • 2. 11.11 Applications of Taylor Series − Evaluate correct to within an error of 0.01. − ∞ (− ) ∞ = = ! = = (− ) ! = − ! + ! − ! + ···
  • 3. 11.11 Applications of Taylor Series − Evaluate correct to within an error of 0.01. − ∞ (− ) ∞ = = ! = = (− ) ! = − ! + ! − ! + ··· − = − · ! + · ! − · ! + ··· +
  • 4. ∞ (− ) ∞ = = ! = = (− ) ! = − ! + ! − ! + ··· − = − · ! + · ! − · ! + ··· +
  • 5. ∞ (− ) ∞ = = ! = = (− ) ! = − ! + ! − ! + ··· − = − · ! + · ! − · ! + ··· + − = − · ! + · ! − · ! + ···
  • 6. ∞ (− ) ∞ = = ! = = (− ) ! = − ! + ! − ! + ··· − = − · ! + · ! − · ! + ··· + − = − · ! + · ! − · ! + ··· = − + − + − ···
  • 7. ∞ (− ) ∞ = = ! = = (− ) ! = − ! + ! − ! + ··· − = − · ! + · ! − · ! + ··· + − = − · ! + · ! − · ! + ··· = − + − + − ··· ≈ .
  • 8. What is the maximum error possible in using the approximation ≈ − ! + ! when − . ≤ ≤ . ? For what value of is this approximation accurate to within . ? What is the smallest degree of the Taylor polynomial we can use to approximate if we want the error in [ . , . ] to be less than ?
  • 9. What is the maximum error possible in using the approximation ≈ − ! + ! when − . ≤ ≤ . ?
  • 10. What is the maximum error possible in using the approximation ≈ − ! + ! when − . ≤ ≤ . ? Taylor’s Inequality: | ( )| | | !
  • 11. What is the maximum error possible in using the approximation ≈ − ! + ! when − . ≤ ≤ . ? Taylor’s Inequality: | ( )| | | ! ( ) | |=|− |≤ , =
  • 12. What is the maximum error possible in using the approximation ≈ − ! + ! when − . ≤ ≤ . ? Taylor’s Inequality: | ( )| | | ! ( ) | |=|− |≤ , = when − . ≤ ≤ .
  • 13. What is the maximum error possible in using the approximation ≈ − ! + ! when − . ≤ ≤ . ? Taylor’s Inequality: | ( )| | | ! ( ) | |=|− |≤ , = when − . ≤ ≤ . . . !
  • 14. For what value of is this approximation accurate to within . ?
  • 15. For what value of is this approximation accurate to within . ? We want | | < . !
  • 16. For what value of is this approximation accurate to within . ? We want | | < . ! | | < . · ! .
  • 17. For what value of is this approximation accurate to within . ? We want | | < . ! | | < . · ! . | |< .
  • 18. What is the smallest degree of the Taylor polynomial we can use to approximate if we want the error in [ . , . ] to be less than ?
  • 19. What is the smallest degree of the Taylor polynomial we can use to approximate if we want the error in [ . , . ] to be less than ? . | ( )| | | . ! !
  • 20. What is the smallest degree of the Taylor polynomial we can use to approximate if we want the error in [ . , . ] to be less than ? . | ( )| | | . ! ! . | ( )| | | . ! !
  • 21. What is the smallest degree of the Taylor polynomial we can use to approximate if we want the error in [ . , . ] to be less than ? . | ( )| | | . ! ! . | ( )| | | . ! ! . | ( )| | | . ! !
  • 22. What is the smallest degree of the Taylor polynomial we can use to approximate if we want the error in [ . , . ] to be less than ? . | ( )| | | . ! ! . | ( )| | | . ! ! . | ( )| | | . ! ! So we need the Taylor polynomial of degree 8.
  • 23. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 24. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 25. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 26. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 27. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 28. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 29. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 30. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 31. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 32. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 33. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 34. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !
  • 35. Taylor approximation of . + = ( ) = + + ··· = ( + )! ! ! !

Notes de l'éditeur

  1. \n
  2. \n
  3. \n
  4. \n
  5. \n
  6. \n
  7. \n
  8. \n
  9. \n
  10. \n
  11. \n
  12. \n
  13. \n
  14. \n
  15. \n
  16. \n
  17. \n
  18. \n
  19. \n
  20. \n
  21. \n
  22. \n
  23. \n
  24. \n
  25. \n
  26. \n
  27. \n
  28. \n
  29. \n