In the case where all the terms are positive,

Slides:



Advertisements
Similar presentations
Solved problems on integral test and harmonic series.
Advertisements

When you see… Find the zeros You think…. To find the zeros...
Section 11.5 – Testing for Convergence at Endpoints.
Section 11.6 – Taylor’s Formula with Remainder
What is the sum of the following infinite series 1+x+x2+x3+…xn… where 0
Calculus I – Math 104 The end is near!. Series approximations for functions, integrals etc.. We've been associating series with functions and using them.
Part 3 Truncation Errors Second Term 05/06.
Part 3 Truncation Errors.
Infinite Series 9 Copyright © Cengage Learning. All rights reserved.
Calculus I – Math 104 The end is near!. 1. Limits: Series give a good idea of the behavior of functions in the neighborhood of 0: We know for other reasons.
Absolute vs. Conditional Convergence Alternating Series and the Alternating Series Test.
Taylor’s Polynomials & LaGrange Error Review
9.3 Taylor’s Theorem: Error Analysis for Series
Infinite Sequences and Series
Does the Series Converge? 10 Tests for Convergence nth Term Divergence Test Geometric Series Telescoping Series Integral Test p-Series Test Direct Comparison.
9.7 and 9.10 Taylor Polynomials and Taylor Series.
Taylor’s Theorem: Error Analysis for Series. Taylor series are used to estimate the value of functions (at least theoretically - now days we can usually.
9.5 Part 1 Ratio and Root Tests
In section 11.9, we were able to find power series representations for a certain restricted class of functions. Here, we investigate more general problems.
Chapter 9.5 ALTERNATING SERIES.
9.3 Taylor’s Theorem: Error Analysis for Series
Absolute vs. Conditional Convergence Alternating Series and the Alternating Series Test.
ALTERNATING SERIES series with positive terms series with some positive and some negative terms alternating series n-th term of the series are positive.
Alternating Series An alternating series is a series where terms alternate in sign.
In this section, we investigate convergence of series that are not made up of only non- negative terms.
Sect. 9-B LAGRANGE error or Remainder
This is an example of an infinite series. 1 1 Start with a square one unit by one unit: This series converges (approaches a limiting value.) Many series.
9.3 Taylor’s Theorem: Error Analysis for Series Tacoma Narrows Bridge: November 7, 1940 Greg Kelly, Hanford High School, Richland, Washington.
9.3 Taylor’s Theorem Quick Review Tell whether the function has derivatives of all orders at the given values of a.
Remainder Theorem. The n-th Talor polynomial The polynomial is called the n-th Taylor polynomial for f about c.
Copyright © Cengage Learning. All rights reserved.
9.3 Taylor’s Theorem: Error Analysis yes no.
Taylor series are used to estimate the value of functions (at least theoretically - now days we can usually use the calculator or computer to calculate.
INFINITE SEQUENCES AND SERIES The convergence tests that we have looked at so far apply only to series with positive terms.
9.5 Alternating Series. An alternating series is a series whose terms are alternately positive and negative. It has the following forms Example: Alternating.
Final Review – Exam 3 Sequences & Series Improper Integrals.
Sequences: All three sequences converge Series: Sequences and Series.
Does the Series Converge?
The Convergence Theorem for Power Series There are three possibilities forwith respect to convergence: 1.There is a positive number R such that the series.
10.3 Convergence of Series with Positive Terms Do Now Evaluate.
Alternating Series and the Alternating Series Test Absolute vs. Conditional Convergence.
INFINITE SEQUENCES AND SERIES In general, it is difficult to find the exact sum of a series.  We were able to accomplish this for geometric series and.
9.7 day 2 Taylor’s Theorem: Error Analysis for Series Tacoma Narrows Bridge: November 7, 1940 Greg Kelly, Hanford High School, Richland, Washington.
Lecture 17 – Sequences A list of numbers following a certain pattern
Section 11.5 – Testing for Convergence at Endpoints
Copyright © Cengage Learning. All rights reserved.
Copyright © Cengage Learning. All rights reserved.
The Taylor Polynomial Remainder (aka: the Lagrange Error Bound)
Copyright © Cengage Learning. All rights reserved.
9.3 Taylor’s Theorem: Error Analysis for Series
Copyright © Cengage Learning. All rights reserved.
Absolute vs. Conditional Convergence
Copyright © Cengage Learning. All rights reserved.
Representation of Functions by Power Series (9.9)
Section 11.6 – Taylor’s Formula with Remainder
Taylor’s Theorem: Error Analysis for Series
11.10 – Taylor and Maclaurin Series
Let A = {image} and B = {image} . Compare A and B.
Find a power series representation for the function {image}
Sec 11.5: ALTERNATING SERIES
Copyright © Cengage Learning. All rights reserved.
ESTIMATING THE SUM OF A SERIES
9.3 Taylor’s Theorem: Error Analysis for Series
Which of the given series is(are) convergent?
Absolute vs. Conditional Convergence
Objectives Approximate a definite integral using the Trapezoidal Rule.
THE INTEGRAL TEST AND ESTIMATES OF SUMS
Alternating convergent series jump over the sum with each partial sum Alternating convergent series jump over the sum with each partial sum. The.
Lagrange Remainder.
Find a power series representation for the function {image}
Presentation transcript:

In the case where all the terms are positive, If we stop evaluating a convergent positive series after adding n terms, the difference between the true infinite sum and our partial sum is called the error or remainder. 𝑅 𝑛 =𝑆− 𝑆 𝑛 In the case where all the terms are positive, the error (or remainder) will be positive. Here’s a representation of the series (Riemann Sum) and it’s related integral for n large. Drawn as a lower sum, the partial sum stops at the last yellow box. The error (shown in red) is less than 𝑛 ∞ 𝑓 𝑥 𝑑𝑥 . Shifted over, drawn as an upper sum, we see that the error is greater than 𝑛+1 ∞ 𝑓 𝑥 𝑑𝑥

Integral Test Remainder Estimate Given 𝑎 𝑛 is a decreasing positive series convergent series and 𝑓 𝑥 is a continuous function where 𝑓 𝑛 = 𝑎 𝑛 then if 𝑅 𝑛 =𝑆− 𝑆 𝑛 𝑛+1 ∞ 𝑓 𝑥 𝑑𝑥 ≤ 𝑅 𝑛 ≤ 𝑛 ∞ 𝑓 𝑥 𝑑𝑥

Example: Approximate the sum of the convergent series using the indicated number of terms. Include an estimate of the maximum error for your approximation.

The minimum number of terms needed is 32. 𝑛=1 ∞ 1 𝑛 3 , 𝑘=3 Example for #43 (read the directions, p. 582) We want 𝑅 𝑛 <.0005 It is sufficient is to find 𝑛 such that 𝑛 ∞ 1 𝑥 3 𝑑𝑥 <.0005 ∞ 𝑛 𝑛 ∞ 1 𝑥 3 𝑑𝑥 =− 1 2 𝑥 −2 = 1 ∞ − −1 2 𝑛 2 = 1 2 𝑛 2 1 2 𝑛 2 <.0005 →1<.001 𝑛 2 →1000< 𝑛 2 →𝑛>31.623 The minimum number of terms needed is 32. 𝑆≈𝑆 32 =1+ 1 8 + 1 27 + 1 64 +…+ 1 32768 ≈1.201583642

Remainder of Alternating Series

𝑛=1 ∞ −1 𝑛+1 𝑛 =1− 1 2 + 1 3 − 1 4 +…+ −1 𝑛+1 𝑛 +… 𝑛=1 ∞ −1 𝑛+1 𝑛 =1− 1 2 + 1 3 − 1 4 +…+ −1 𝑛+1 𝑛 +… Let’s look at some partial sums graphically. Clearly, the Partial Sums are headed for some limit in the middle of these points. Each “jump” is smaller than the previous one.

We know that the infinite sum 𝑆 is between What if we stopped at 𝑆 5 ? We know that the infinite sum 𝑆 is between 𝑆 5 =1− 1 2 + 1 3 − 1 4 + 1 5 = 47 60 and the next partial sum 𝑆 6 = 𝑆 5 − 1 6 = 37 60 So if I use 𝑆 5 = 47 60 as an estimate for 𝑆, my error is less than | 𝑎 6 |= 1 6 . How far off can my estimate be if I use 𝑆 11 for my estimate? 𝑆 100 ? 𝑎 12 = 1 12 , and |𝑎 101 |= 1 101 respectively.

Example

LaGrange Remainder Theorem The difference between 𝑓 𝑥 and 𝑝 𝑛 (𝑥) is 𝑅 𝑛 𝑥 = 𝑓 𝑛+1 (𝑧) 𝑛+1 ! 𝑥−𝑎 𝑛+1 where 𝑧 is some unknowable number between 𝑥 𝑎𝑛𝑑 𝑎. 𝑎 is the 𝑥−𝑐𝑜𝑜𝑟𝑑𝑖𝑛𝑎𝑡𝑒 at the point of tangency.

𝑓 𝑥 = 1 1−𝑥 , 𝑛=4 EX: #4 𝑓 𝑥 = 1 1−𝑥 →𝑓 0 =1 𝑓 ′ 𝑥 =−(1−𝑥 ) −2 −1 =(1−𝑥 ) −2 → 𝑓 ′ 0 =1 𝑓 ′′ 𝑥 =−2(1−𝑥 ) −3 −1 =2(1−𝑥 ) −3 → 𝑓 ′ ′ 0 =2 𝑓 ′ ′′ 𝑥 =−6(1−𝑥 ) −4 −1 =6(1−𝑥 ) −4 → 𝑓 ′ ′′ 0 =6 𝑓 (4) 𝑥 =−24(1−𝑥 ) −5 −1 =24(1−𝑥 ) −5 → 𝑓 4 0 =24 𝑝 4 𝑥 =𝑓 0 + 𝑓 ′ 0 𝑥+ 𝑓 ′′ 0 2! 𝑥 2 + 𝑓 ′′′ 0 3! 𝑥 3 + 𝑓 4 0 4! 𝑥 4 𝑝 4 𝑥 =1+1𝑥+ 2 2! 𝑥 2 + 6 3! 𝑥 3 + 24 4! 𝑥 4 𝑝 4 𝑥 =1+𝑥+ 𝑥 2 + 𝑥 3 + 𝑥 4 Look familiar? 1+r+ 𝑟 2 +𝑟 3 +…+ 𝑟 𝑛 +…= 1 1−𝑟 , 𝑖𝑓 𝑟 <1

𝑅 𝑛 𝑥 = 𝑓 𝑛+1 (𝑧) 𝑛+1 ! 𝑥−𝑎 𝑛+1 𝑎=0, 𝑛=4, 𝑓 5 𝑧 =5!(1−𝑧 ) −6 𝑅 4 𝑥 = 𝑓 5 (𝑧) 5 ! 𝑥−0 5 = 5!(1−𝑧 ) −6 5 ! 𝑥 5 =(1−𝑧 ) −6 𝑥 5

We will need four derivatives all evaluated at 𝑥=0. 𝑓 𝑥 =𝑠𝑖𝑛𝑥, 𝑛=3 We will need four derivatives all evaluated at 𝑥=0. 𝑓 𝑥 =𝑠𝑖𝑛𝑥→𝑓 0 =0 𝑓 ′ 𝑥 =𝑐𝑜𝑠𝑥→ 𝑓 ′ 0 =1 𝑓 ′′ 𝑥 =−𝑠𝑖𝑛𝑥→ 𝑓 ′′ 0 =0 𝑓 ′′′ 𝑥 =−𝑐𝑜𝑠𝑥→ 𝑓 ′′′ 0 =−1 𝑓 4 𝑥 =𝑠𝑖𝑛𝑥→ 𝑓 4 𝑥 =0 𝑝 3 𝑥 =𝑓 0 + 𝑓 ′ 0 𝑥+ 𝑓 ′′ 0 2! 𝑥 2 + 𝑓 ′′′ 0 3! 𝑥 3 =0+1𝑥+ 0 2! 𝑥 2 + −1 3! 𝑥 3 𝑓 𝑥 =𝑠𝑖𝑛𝑥 ≈ 𝑝 3 𝑥 =𝑥− 1 3! 𝑥 3 𝑅 𝑛 𝑥 = 𝑓 𝑛+1 (𝑧) 𝑛+1 ! 𝑥−𝑎 𝑛+1 𝑅 3 𝑥 = 𝑓 4 (𝑧) 4 ! 𝑥−0 4 = sin 𝑧 4 ! 𝑥 4