The p-Series and Estimating Series Value

Learning Outcomes

  • Estimate the value of a series by finding bounds on its remainder term

The p-Series

The harmonic series n=11nn=11n and the series n=11n2n=11n2 are both examples of a type of series called a p-series.

Definition


For any real number pp, the series

n=11npn=11np

 

is called a p-series.

We know the p-series converges if p=2p=2 and diverges if p=1p=1. What about other values of p?p? In general, it is difficult, if not impossible, to compute the exact value of most pp -series. However, we can use the tests presented thus far to prove whether a pp -series converges or diverges.

If p<0p<0, then 1np1np, and if p=0p=0, then 1np11np1. Therefore, by the divergence test,

n=11np diverges if p0n=11np diverges if p0.

 

If p>0p>0, then f(x)=1xpf(x)=1xp is a positive, continuous, decreasing function. Therefore, for p>0p>0, we use the integral test, comparing

n=11np and 11xpdxn=11np and 11xpdx.

 

We have already considered the case when p=1p=1. Here we consider the case when p>0,p1p>0,p1. For this case,

11xpdx=limbb11xpdx=limb11px1p|b1=limb11p[b1p1]11xpdx=limbb11xpdx=limb11px1p|b1=limb11p[b1p1].

 

Because

b1p0 if p>1 and b1p if p<1b1p0 if p>1 and b1p if p<1,

 

we conclude that

11xpdx={1p1 if p>1 if p<111xpdx={1p1 if p>1 if p<1

 

Therefore, n=11npn=11np converges if p>1p>1 and diverges if [latex]0

In summary,

n=11np{ converges if p>1 diverges if p1n=11np{ converges if p>1 diverges if p1

 

Example: Testing for Convergence of p-series

For each of the following series, determine whether it converges or diverges.

  1. n=11n4n=11n4
  2. n=11n23n=11n23

try it

Does the series n=11n54n=11n54 converge or diverge?

Watch the following video to see the worked solution to the above Try It.

For closed captioning, open the video on its original page by clicking the Youtube logo in the lower right-hand corner of the video display. In YouTube, the video will begin at the same starting point as this clip, but will continue playing until the very end.

You can view the transcript for this segmented clip of “5.3.4” here (opens in new window).

Estimating the Value of a Series

Suppose we know that a series n=1ann=1an converges and we want to estimate the sum of that series. Certainly we can approximate that sum using any finite sum Nn=1anNn=1an where NN is any positive integer. The question we address here is, for a convergent series n=1ann=1an, how good is the approximation Nn=1an?Nn=1an? More specifically, if we let

RN=n=1anNn=1anRN=n=1anNn=1an

 

be the remainder when the sum of an infinite series is approximated by the NthNth partial sum, how large is RN?RN? For some types of series, we are able to use the ideas from the integral test to estimate RNRN.

theorem: Remainder Estimate from the Integral Test


Suppose n=1ann=1an is a convergent series with positive terms. Suppose there exists a function ff satisfying the following three conditions:

  1. ff is continuous,
  2. ff is decreasing, and
  3. f(n)=anf(n)=an for all integers n1n1.

Let SNSN be the Nth partial sum of n=1ann=1an. For all positive integers NN,

SN+N+1f(x)dx<n=1an<SN+Nf(x)dxSN+N+1f(x)dx<n=1an<SN+Nf(x)dx.

 

In other words, the remainder RN=n=1anSN=n=N+1an satisfies the following estimate:

N+1f(x)dx<RN<Nf(x)dx.

 

This is known as the remainder estimate.

We illustrate the Remainder Estimate from the Integral Test in Figure 4. In particular, by representing the remainder RN=aN+1+aN+2+aN+3+ as the sum of areas of rectangles, we see that the area of those rectangles is bounded above by Nf(x)dx and bounded below by N+1f(x)dx. In other words,

RN=aN+1+aN+2+aN+3+>N+1f(x)dx

 

and

RN=aN+1+aN+2+aN+3+<Nf(x)dx.

 

We conclude that

N+1f(x)dx<RN<Nf(x)dx.

 

Since

n=1an=SN+RN,

 

where SN is the Nth partial sum, we conclude that

SN+N+1f(x)dx<n=1an<SN+Nf(x)dx.

 

This shows two graphs side by side of the same decreasing concave up function y = f(x) that approaches the x-axis in quadrant 1. Rectangles are drawn with a base of 1 over the intervals N through N + 4. The heights of the rectangles in the first graph are determined by the value of the function at the right endpoints of the bases, and those in the second graph are determined by the value at the left endpoints of the bases. The areas of the rectangles are marked: a_(N + 1), a_(N + 2), through a_(N + 4).

Figure 4. Given a continuous, positive, decreasing function f and a sequence of positive terms an such that an=f(n) for all positive integers n, (a) the areas aN+1+aN+2+aN+3+<Nf(x)dx, or (b) the areas aN+1+aN+2+aN+3+>N+1f(x)dx. Therefore, the integral is either an overestimate or an underestimate of the error.

Example: Estimating the Value of a Series

Consider the series n=11n3.

  1. Calculate S10=10n=11n3 and estimate the error.
  2. Determine the least value of N necessary such that SN will estimate n=11n3 to within 0.001.

S10=1+123+133+143++11031.19753.



By the remainder estimate, we know

RN<N1x3dx.



We have

101x3dx=limbb101x3dx=limb[12x2]bN=limb[12b2+12N2]=12N2.



Therefore, the error is R10<12(10)2=0.005.

  • Find N such that RN<0.001. In part a. we showed that RN<12N2. Therefore, the remainder RN<0.001 as long as 12N2<0.001. That is, we need 2N2>1000. Solving this inequality for N, we see that we need N>22.36. To ensure that the remainder is within the desired amount, we need to round up to the nearest integer. Therefore, the minimum necessary value is N=23.

 

try it

For n=11n4, calculate S5 and estimate the error R5.