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Coordinated Calculus

Section 7.6 Absolute Convergence and Error Bounds

When dealing with alternating series, there are a couple significant questions we would like to answer. First, can we approximate what the value of the sum of a convergent alternating series is? If so, how close is our estimate? Second, is there any connection between an alternating series and the related series with the similar series whose terms are all positive? In this section, we confront these questions.

Subsection 7.6.1 Estimating Alternating Sums

If the series converges, the argument for the Alternating Series Test also provides us with a method to determine how close the nth partial sum Sn is to the actual sum of the series. To see how this works, let S be the sum of a convergent alternating series, so
S=k=1(1)kak.
Recall that the sequence of partial sums oscillates around the sum S so that
|SSn|<|Sn+1Sn|=an+1.
Therefore, the value of the term an+1 provides an error estimate for how well the partial sum Sn approximates the actual sum S. We summarize this fact in the statement of the Alternating Series Estimation Theorem.

Alternating Series Estimation Theorem.

Let {ak} be a sequence of positive terms that decreases to 0 as k, so that the alternating series k=1(1)k+1ak converges to a number S. If Sn=k=1n(1)k+1ak is the nth partial sum of the alternating series, then
|SSn|an+1.

Example 7.41.

Determine how well the 100th partial sum S100 of
k=1(1)k+1k
approximates the sum of the series.
Solution.
If we let S be the sum of the series k=1(1)k+1k, then we know that
|S100S|<a101.
Now
a101=11010.0099,
so the 100th partial sum is within 0.0099 of the sum of the series. We have discussed the fact (and will later verify) that
S=k=1(1)k+1k=ln(2),
and so S0.693147 while
S100=k=1100(1)k+1k0.6881721793
.
We see that the actual difference between S and S100 is approximately 0.0049750013, which is indeed less than 0.0099.

Example 7.42.

Determine the number of terms it takes to approximate the sum of the convergent alternating series
k=1(1)k+1k4
to within 0.0001.
Answer.
S100.9469925924; 7720π40.9470328299.
Solution.
First note that the sequence {1k4} decreases to 0, so the series k=1(1)k+1k4 converges by the Alternating Series Test. Let S be the sum k=1(1)k+1k4 and Sn the nth partial sum of the series. We know that
|SSn|<an+1=1(n+1)4.
So we only need to determine the value of n so that
1(n+1)4<0.0001.
This happens when (n+1)4<10000 or when n+1>10. So n=10 will do. A computer algebra system gives S100.9469925924 while 7720π40.9470328299. These do agree to 0.0001.

Subsection 7.6.2 Absolute and Conditional Convergence

A series such as
(7.16)11419+116+125+1361491641811100+
whose terms are neither all nonnegative nor alternating is different from any series that we have considered so far. The behavior of such a series can be rather complicated, but there is an important connection between a series with some negative terms and series with all positive terms.

Example 7.43.

  1. Explain why the series
    11419+116+125+1361491641811100+
    must have a sum that is less than the series
    k=11k2.
  2. Explain why the series
    11419+116+125+1361491641811100+
    must have a sum that is greater than the series
    k=11k2.
  3. Given that the terms in the series
    11419+116+125+1361491641811100+
    converge to 0, what do you think the previous two results tell us about the convergence status of this series?
Answer.
  1. 11419+116+125+1361491641811100+<k=11k2.
  2. 11419+116+125+1361491641811100+>k=11k2.
  3. We expect this series to converge to some finite number between k=11k2 and k=11k2.
Solution.
  1. Each term in the series
    11419+116+125+1361491641811100+
    is of the form 1k2 or 1k2. Since each of these terms is less than or equal to 1k2 it follows that
    11419+116+125+1361491641811100+<k=11k2
    .
  2. Each term in the series
    11419+116+125+1361491641811100+
    is of the form 1k2 or 1k2. Since each of these terms is greater than or equal to 1k2 it follows that
    11419+116+125+1361491641811100+>k=11k2
    .
  3. We know that k=11k2 is a p-series with p=2>1 and so is a convergent series. Since k=11k2=k=11k2, the series k=11k2 also converges. Since the terms in the series
    11419+116+125+1361491641811100+
    converge to 0 and the series itself is bounded between two convergent series, we should expect this series to converge to some finite number between k=11k2 and k=11k2.
As the example in Example 7.43 suggests, if a series ak has some negative terms but |ak| converges, then the original series, ak, must also converge. That is, if |ak| converges, then so must ak.
As we just observed, this is the case for the series (7.16), because the corresponding series of the absolute values of its terms is the convergent p-series 1k2. But there are series, such as the alternating harmonic series (1)k+11k, that converge while the corresponding series of absolute values, 1k, diverges. We distinguish between these behaviors by introducing the following language.

Absolute vs. Conditional Convergence.

Consider a series ak.
  1. The series ak converges absolutely (or is absolutely convergent) provided that |ak| converges.
  2. The series ak converges conditionally (or is conditionally convergent) provided that |ak| diverges and ak converges.
In this terminology, the series (7.16) converges absolutely while the alternating harmonic series converges conditionally. Absolute convergence is a strong condition in that it implies convergence. That is, if the series |ak| converges, then the series ak converges as well. The converse is not true, as the alternating harmonic series shows.

Absolute Convergence Implies Convergence.

If a series k=1ak converges absolutely, then it converges in the usual sense. That is, if the series k=1|ak| converges, then k=1ak converges as well.

Example 7.44.

  1. Consider the series (1)kln(k)k.
    1. Does this series converge? Explain.
    2. Does this series converge absolutely? Explain what test you use to determine your answer.
  2. Consider the series (1)kln(k)k2.
    1. Does this series converge? Explain.
    2. Does this series converge absolutely? Hint: Use the fact that ln(k)<k for large values of k and then compare to an appropriate p-series.
Answer.
    1. (1)kln(k)k converges.
    2. (1)kln(k)k converges conditionally.
    1. (1)kln(k)k2 converges.
    2. (1)kln(k)k2 converges absolutely.
Solution.
    1. By L’Hopital’s Rule we have
      limkln(k)k=limk1k=0.
      Also, ddkln(k)k=1ln(k)k2 is negative when k>e, so the sequence {ln(k)k} ultimately decreases to 0. Since the first few terms in a series are irrelevant to its convergence or divergence, we conclude that the series (1)kln(k)k converges by the Alternating Series test.
    2. Note that
      limt1tln(x)x=limtln(x)22|1t=limtln(t)22=limtln(t)22=.
      Since the improper integral diverges, the Integral Test shows that the series (1)kln(k)k diverges. So the series (1)kln(k)k converges conditionally.
    1. By L’Hopital’s Rule we have
      limkln(k)k2=limk12k2=0.
      Also,
      ddkln(k)k2=k2kln(k)k4=12ln(k)k3
      is negative when k>e, so the sequence {ln(k)k2} ultimately decreases to 0. Since the first few terms in a series are irrelevant to its convergence or divergence, we conclude that the series (1)kln(k)k2 converges by the Alternating Series test.
    2. Notice that
      limkln(k)k1/2=limk2k1/2=0,
      So 1k dominates ln(k) and ln(k)<k for large k. It follows that
      ln(k)k2<kk2=1k3/2
      for large k. Therefore,
      ln(k)k2<1k3/2
      for large k. Since 1k3/2 is a p-series with p=32>1, the series 1k3/2 converges. This forces the series ln(k)k2 to converge as well, by the direct comparison test. So (1)kln(k)k2 converges absolutely.
Conditionally convergent series turn out to be very interesting. If the sequence {an} decreases to 0, but the series ak diverges, the conditionally convergent series (1)kak is right on the borderline of being a divergent series. As a result, any conditionally convergent series converges very slowly. Furthermore, some very strange things can happen with conditionally convergent series, as illustrated in some of the exercises.

Subsection 7.6.3 Summary of Tests for Convergence of Series

Convergence Test Summary.

We have discussed several tests for convergence/divergence of series in our sections and in exercises. We close this section of the text with a summary of all the tests we have encountered, followed by an example that challenges you to decide which convergence test to apply to several different series.
Geometric Series
The geometric series ark with ratio r converges for 1<r<1 and diverges for |r|1.
The sum of the convergent geometric series k=0ark is a1r.
Divergence Test
If the sequence an does not converge to 0, then the series ak diverges.
This is the first test to apply because the conclusion is simple. However, if limnan=0, no conclusion can be drawn.
Integral Test
Let f be a positive, decreasing function on an interval [c,) and let ak=f(k) for each positive integer kc.
  • If cf(t) dt converges, then ak converges.
  • If cf(t) dt diverges, then ak diverges.
Use this test when f(x) is easy to integrate.
Direct Comp. Test
(see Ex 4 in Section 7.3)
Let 0akbk for each positive integer k.
  • If bk converges, then ak converges.
  • If ak diverges, then bk diverges.
Use this test when you have a series with known behavior that you can compare to — this test can be difficult to apply.
Limit Comp. Test
Let an and bn be sequences of positive terms. If
limkakbk=L
for some positive finite number L, then the two series ak and bk either both converge or both diverge.
Easier to apply in general than the comparison test, but you must have a series with known behavior to compare. Useful to apply to series of rational functions.
Ratio Test
Let ak0 for each k and suppose
limk|ak+1||ak|=r
  • If r<1, then the series ak converges absolutely.
  • If r>1, then the series ak diverges.
  • If r=1, then test is inconclusive.
This test is useful when a series involves factorials and powers.
Root Test
(see Exercise 2 in Section 7.3)
Let ak0 for each k and suppose
limkakk=r.
  • If r<1, then the series ak converges.
  • If r>1, then the series ak diverges.
  • If r=1, then test is inconclusive.
In general, the Ratio Test can usually be used in place of the Root Test. However, the Root Test can be quick to use when ak involves kth powers.
Alt. Series Test
If an is a positive, decreasing sequence so that limnan=0, then the alternating series (1)k+1ak converges.
This test applies only to alternating series — we assume that the terms an are all positive and that the sequence {an} is decreasing.
Alt. Series Est.
Let Sn=k=1n(1)k+1ak be the nth partial sum of the alternating series k=1(1)k+1ak. Assume an>0 for each positive integer n, the sequence an decreases to 0 and limnSn=S. Then it follows that |SSn|<an+1.
This bound can be used to determine the accuracy of the partial sum Sn as an approximation of the sum of a convergent alternating series.

Example 7.45.

For (a)-(j), use appropriate tests to determine the convergence or divergence of the following series. Throughout, if a series is a convergent geometric series, find its sum.
  1. k=3 2k2
  2. k=1 k1+2k
  3. k=0 2k2+1k3+k+1
  4. k=0 100kk!
  5. k=1 2k5k
  6. k=1 k31k5+1
  7. k=2 3k17k
  8. k=2 1kk
  9. k=1 (1)k+1k+1
  10. k=2 1kln(k)
  11. Determine a value of n so that the nth partial sum Sn of the alternating series n=2(1)nln(n) approximates the sum to within 0.001.
Answer.
  1. k=3 2k2 diverges.
  2. k=1 k1+2k diverges.
  3. k=0 2k2+1k3+k+1 diverges.
  4. k=0 100kk! converges.
  5. k=1 2k5k is a geometric series with ratio 25 and sum 23.
  6. k=1 k31k5+1 converges.
  7. k=2 3k17k is a convergent geometric series with a=349 and r=37 and sum 328.
  8. k=2 1kk converges.
  9. k=1 (1)k+1k+1 converges.
  10. k=2 1kln(k) diverges.
  11. k=2(1)kln(k) converges very slowly.
Solution.
  1. For large values of k, 2k2 looks like 2k. We will use the Limit Comparison Test to compare these two series:
    limk2k22k=limkkk2=limk112k=1.
    Since this limit is a positive constant, we know that the two series k=3 2k2 and k=3 2k either both converge or both diverge. Now k=3 2k=2k=3 1k1/2 is constant times a p-series with p=12, so k=3 2k diverges. Therefore, k=3 2k2 diverges as well.
  2. Note that
    limkk1+2k=limkk2k=12,
    so the Divergence Test shows that k=1 k1+2k diverges.
  3. For large values of k, 2k2+1k3+k+1 looks like 2k. We will use the Limit Comparison Test to compare these two series:
    limk2k2+1k3+k+12k=limk(2k2+1)k2(k3+k+1)=limk2+1k22+1k2+1k3=1.
    Since this limit is a positive constant, we know that the two series k=1 2k2+1k3+k+1 and k=1 2k either both converge or both diverge. Now k=1 2k=2k=1 1k is constant times a p-series with p=1, so k=1 2k diverges. Therefore, k=0 2k2+1k3+k+1 diverges as well.
  4. Series that involve factorials are good candidates for the Ratio Test:
    limk100k+1(k+1)!100kk!=limk100k+1k!100k(k+1)!=limk100k+1=0.
    Since this limit is 0, the Ratio Test tells us that the series k=0 100kk! converges.
  5. Notice that k=1 2k5k=k=1 (25)k is a geometric series with ratio 25. Let’s write out the first few terms to identify the value of a:
    k=1 (25)k=25+(25)2+(25)3+=(25)[1+25+(25)2+].
    So a=25. Since the ratio of this geometric series is between 1 and 1, the series converges. The sum of the series is
    k=1 2k5k=(25)(1125)=(25)(53)=23
    .
  6. For large values of n, k31k5+1 looks like k3k5=1k2. We will use the Limit Comparison Test to compare k=1 k31k5+1 and k=1 1k2:
    limkk31k5+11k2=limkk5k2k5+1=limk11k31+1k5=1.
    Since this limit is 1, we know that the two series k=1 k31k5+1 and k=1 1k2 either both converge or both diverge. Now k=1 1k2 is a p-series with p=2, so k=1 1k2 converges. Therefore, k=1 k31k5+1 converges as well.
  7. This series looks geometric, but to be sure let’s write out the first few terms of this series:
    k=2 3k17k=372+3273+3374+=(372)[1+37+(37)2+(37)3+].
    So k=2 3k17k is a geometric series with a=349 and r=37. Since the ratio of this geometric series is between 1 and 1, the series converges. The sum of the series is
    k=2 3k17k=(349)(1137)=(349)(74)=328.
  8. k=2 1kk converges by direct comparison with the series k=2 1k2. Note that for all k2, we have kkk2, so 1kk1k2. Since k=21k2 is a convergent p-series with p=2, then by the direct comparison test, k=21kk also converges.
  9. This series is an alternating series of the form k=1(1)k+1ak with ak=1k+1. Since
    limk1k+1=0
    and 1k+1 decreases to 0, the Alternating Series Test shows that k=1 (1)k+1k+1 converges.
  10. For this example we will use the Integral Test with the substitution w=ln(x), dw=1x dx:
    21xln(x) dx=limb2b1xln(x) dx=limbln(2)ln(b)1w dw=limbln(w)|ln(2)ln(b)=limb[ln(ln(b))ln(ln(2))]=.
    Since 21xln(x) dx diverges, we conclude k=2 1kln(k) diverges.
  11. First note that the terms 1ln(k) decrease to 0, so the Alternating Series Test shows that the alternating series k=2(1)kln(k) converges. Let S=k=2(1)kln(k) and let Sn be the nth partial sum of this series. Recall that
    |SnS|<|SnSn+1|=an+1
    where an+1=1ln(n+1). If we can find a value of n so that an+1<0.001, then |SnS|<0.001 as desired. Now
    an+1<0.0011ln(n+1)<0.001ln(n+1)>1000n+1>e1000n>e10001.
    So if we choose n=e1000, then Sn approximates the sum of the series to within 0.001. Notice that e10001.97×10434 is a very large number. This shows that the series k=2(1)kln(k) converges very slowly.

Subsection 7.6.4 Summary

  • The difference between the (n1)th partial sum Sn1 and the nth partial sum Sn of a convergent alternating series k=1(1)kak is |SnSn1|=an. Since the partial sums oscillate around the sum S of the series, it follows that
    |SSn|<an.
    So the nth partial sum of a convergent alternating series k=1(1)kak approximates the actual sum of the series to within an.
  • The convergence of an alternating series may relate to the convergence of the related series whose terms are all positive. Indeed, if an alternating series converges absolutely, then it also converges. However, an alternating series may converge even when the series with all positive terms diverges -- this is called conditional convergence.

Exercises 7.6.5 Exercises

1. Estimating the sum of an alternating series.

For the following alternating series,
n=1an=0.45(0.45)33!+(0.45)55!(0.45)77!+...
how many terms do you have to compute in order for your approximation (your partial sum) to be within 0.0000001 from the convergent value of that series?

2. Estimating the sum of a different alternating series.

For the following alternating series,
n=1an=1(0.4)22!+(0.4)44!(0.4)66!+(0.4)88!...
how many terms do you have to go for your approximation (your partial sum) to be within 0.0000001 from the convergent value of that series?

3. Estimating the sum of one more alternating series.

For the following alternating series,
n=1an=1110+110011000+...
how many terms do you have to go for your approximation (your partial sum) to be within 1e-06 from the convergent value of that series?

4. A series that converges conditionally and slowly.

Conditionally convergent series converge very slowly. As an example, consider the famous formula
 8 
We will derive this formula in upcoming work.
(7.17)π4=113+1517+=k=0(1)k12k+1
In theory, the partial sums of this series could be used to approximate π.
  1. Show that the series in (7.17) converges conditionally.
  2. Let Sn be the nth partial sum of the series in (7.17). Calculate the error in approximating π4 with S100 and explain why this is not a very good approximation.
  3. Determine the number of terms it would take in the series (7.17) to approximate π4 to 10 decimal places. (The fact that it takes such a large number of terms to obtain even a modest degree of accuracy is why we say that conditionally convergent series converge very slowly.)

5. A alternative approximation method for convergent alternating series.

We have shown that if (1)k+1ak is a convergent alternating series, then the sum S of the series lies between any two consecutive partial sums Sn. This suggests that the average Sn+Sn+12 is a better approximation to S than is Sn.
  1. Show that Sn+Sn+12=Sn+12(1)n+2an+1.
  2. Use this revised approximation in (a) with n=20 to approximate ln(2) given that
    ln(2)=k=1(1)k+11k.
    Compare this to the approximation using just S20. For your convenience, S20=155685007232792560.

6. A surprising result about the rearrangement of terms in conditionally convergent series.

Conditionally convergent series exhibit interesting and unexpected behavior. In this exercise we examine the conditionally convergent alternating harmonic series k=1(1)k+1k and discover that addition is not commutative for conditionally convergent series. We will also encounter Riemann’s Theorem concerning rearrangements of conditionally convergent series. Before we begin, we remind ourselves that
k=1(1)k+1k=ln(2),
a fact which will be verified in a later section.
  1. First we make a quick analysis of the positive and negative terms of the alternating harmonic series.
    1. Show that the series k=112k diverges.
    2. Show that the series k=112k+1 diverges.
    3. Based on the results of the previous parts of this exercise, what can we say about the sums k=C12k and k=C12k+1 for any positive integer C? Be specific in your explanation.
  2. Recall addition of real numbers is commutative; that is
    a+b=b+a
    for any real numbers a and b. This property is valid for any sum of finitely many terms, but does this property extend when we add infinitely many terms together?
    The answer is no, and something even more odd happens. Riemann’s Theorem (after the nineteenth-century mathematician Georg Friedrich Bernhard Riemann) states that a conditionally convergent series can be rearranged to converge to any prescribed sum. More specifically, this means that if we choose any real number S, we can rearrange the terms of the alternating harmonic series k=1(1)k+1k so that the sum is S. To understand how Riemann’s Theorem works, let’s assume for the moment that the number S we want our rearrangement to converge to is positive. Our job is to find a way to order the sum of terms of the alternating harmonic series to converge to S.
    1. Explain how we know that, regardless of the value of S, we can find a partial sum P1
      P1=k=1n112k+1=1+13+15++12n1+1
      of the positive terms of the alternating harmonic series that equals or exceeds S. Let
      S1=P1.
    2. Explain how we know that, regardless of the value of S1, we can find a partial sum N1
      N1=k=1m112k=12141612m1
      so that
      S2=S1+N1S
      .
    3. Explain how we know that, regardless of the value of S2, we can find a partial sum P2
      P2=k=n1+1n212k+1=12(n1+1)+1+12(n1+2)+1++12n2+1
      of the remaining positive terms of the alternating harmonic series so that
      S3=S2+P2S
      .
    4. Explain how we know that, regardless of the value of S3, we can find a partial sum
      N2=k=m1+1m212k=12(m1+1)12(m1+2)12m2
      of the remaining negative terms of the alternating harmonic series so that
      S4=S3+N2S
      .
    5. Explain why we can continue this process indefinitely and find a sequence {Sn} whose terms are partial sums of a rearrangement of the terms in the alternating harmonic series so that limnSn=S.

7. Determine whether a series is absolutely convergent, conditionally convergent, or divergent.

Determine whether the following alternating series are absolutely convergent, conditionally convergent, or divergent. Answer "Absolutely Convergent", "Conditionally Convergent", or "Divergent".
  • choose one
  • Absolutely Convergent
  • Conditionally Convergent
  • Divergent
1. n=1(1)n14n5
  • choose one
  • Absolutely Convergent
  • Conditionally Convergent
  • Divergent
2. n=1(1)n5n13n+2
  • choose one
  • Absolutely Convergent
  • Conditionally Convergent
  • Divergent
3. n=1(1)n+1n1n26
Note: You only have two attempts at this problem.

8. Practice deciding which convergence tests to use.

Select the FIRST correct reason why the given series converges.

9. Practice determining series convergence.

Determine whether the following series converge or diverge. Answer "Converges" or "Diverges."
  • Converges
  • Diverges
1. n=1n(53)n
  • Converges
  • Diverges
2. n=1n!100n
  • Converges
  • Diverges
3. n=1sin6n6n
Note: You only have two attempts at this problem.