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Sequences and Series

Sequences (CED BC Unit 10)

A sequence is an ordered list of numbers: a1,a2,a3,a_1, a_2, a_3, \ldots. Formally, a sequence is a Function from the positive integers (or a subset thereof) to the real numbers: a ⁣:NRa \colon \mathbb{N} \to \mathbb{R}Written as {an}n=1\{a_n\}_{n=1}^{\infty} or {an}\{a_n\}.

A sequence {an}\{a_n\} converges to a limit LL if:

limnan=L\lim_{n \to \infty} a_n = L

This means: for every ϵ>0\epsilon \gt 0There exists an integer NN such that anL<ϵ|a_n - L| \lt \epsilon for all nNn \ge N. The terms eventually get and stay arbitrarily close to LL.

If no such limit exists, the sequence diverges.

Bounded and Monotone Sequences

  • Bounded above: anMa_n \le M for all nn and some MM.
  • Bounded below: anma_n \ge m for all nn and some mm.
  • Bounded: bounded both above and below.
  • Monotone increasing: an+1ana_{n+1} \ge a_n for all nn.
  • Monotone decreasing: an+1ana_{n+1} \le a_n for all nn.
  • Eventually monotone: the monotonicity holds for all nn beyond some index NN.

Monotone Convergence Theorem. Every bounded monotone sequence converges. This is one of the most Powerful existence theorems in analysis: it guarantees convergence without requiring you to find the Limit explicitly.

Corollary: A monotone increasing sequence that is not bounded above diverges to ++\infty. A Monotone decreasing sequence that is not bounded below diverges to -\infty.

Common Sequences

| Sequence | Convergence | Limit | | -------------------------------------- | ----------- | ------- | --------- | --- | | an=1na_n = \frac{1}{n} | Converges | 00 | | an=rna_n = r^n (r<1 | r | \lt 1) | Converges | 00 | | an=rna_n = r^n (r1 | r | \ge 1) | Diverges | — | | an=(1+1n)na_n = \left(1 + \frac{1}{n}\right)^n | Converges | ee | | an=n!nna_n = \frac{n!}{n^n} | Converges | 00 | | an=(1)na_n = (-1)^n | Diverges | — | | an=n+1na_n = \sqrt{n+1} - \sqrt{n} | Converges | 00 | | an=lnnna_n = \frac{\ln n}{n} | Converges | 00 |

Proof: n!nn0\frac{n!}{n^n} \to 0

Write out the terms:

0<n!nn=123nnnnn=1n2n3nnn0 \lt \frac{n!}{n^n} = \frac{1 \cdot 2 \cdot 3 \cdots n}{n \cdot n \cdot n \cdots n} = \frac{1}{n} \cdot \frac{2}{n} \cdot \frac{3}{n} \cdots \frac{n}{n}

The first n/2\lfloor n/2 \rfloor factors are each at most 12\frac{1}{2}So:

0<n!nn(12)n/200 \lt \frac{n!}{n^n} \le \left(\frac{1}{2}\right)^{\lfloor n/2 \rfloor} \to 0

By the squeeze theorem, n!nn0\frac{n!}{n^n} \to 0.

Proof: lnnn0\frac{\ln n}{n} \to 0

Since lnn\ln n grows slower than any positive power of nnWe have lnn<n\ln n \lt \sqrt{n} for Sufficiently large nn. Therefore 0<lnnn<nn=1n0 \lt \frac{\ln n}{n} \lt \frac{\sqrt{n}}{n} = \frac{1}{\sqrt{n}}And 1n0\frac{1}{\sqrt{n}} \to 0 So by the squeeze theorem, lnnn0\frac{\ln n}{n} \to 0.

Series (CED BC Unit 10)

An infinite series is the sum of the terms of an infinite sequence:

n=1an=a1+a2+a3+\sum_{n=1}^{\infty} a_n = a_1 + a_2 + a_3 + \cdots

Partial Sums

The nnTh partial sum is Sn=k=1nakS_n = \sum_{k=1}^{n} a_k. The series converges if and only if the Sequence of partial sums {Sn}\{S_n\} converges:

n=1an=L    limnSn=L\sum_{n=1}^{\infty} a_n = L \iff \lim_{n \to \infty} S_n = L

If {Sn}\{S_n\} diverges, the series diverges.

The nnTh-Term Test (Divergence Test)

If limnan0\displaystyle\lim_{n \to \infty} a_n \ne 0Then an\displaystyle\sum a_n diverges.

Proof (by contrapositive): If an\sum a_n converges to LLThen SnLS_n \to L and Sn1LS_{n-1} \to L. Since an=SnSn1a_n = S_n - S_{n-1}We get anLL=0a_n \to L - L = 0.

Caution: If limnan=0\displaystyle\lim_{n \to \infty} a_n = 0The test is inconclusive. The series may Converge or diverge. The harmonic series 1n\sum \frac{1}{n} is the canonical counterexample.

Example

Does n=1nn+1\displaystyle\sum_{n=1}^{\infty} \frac{n}{n+1} converge?

limnnn+1=10\lim_{n \to \infty} \frac{n}{n+1} = 1 \ne 0

By the nnTh-term test, the series diverges.

The Harmonic Series

n=11n=1+12+13+14+\sum_{n=1}^{\infty} \frac{1}{n} = 1 + \frac{1}{2} + \frac{1}{3} + \frac{1}{4} + \cdots

Even though 1n0\frac{1}{n} \to 0This series diverges. The proof groups terms:

1+12+(13+14)+(15+16+17+18)+1 + \frac{1}{2} + \left(\frac{1}{3} + \frac{1}{4}\right) + \left(\frac{1}{5} + \frac{1}{6} + \frac{1}{7} + \frac{1}{8}\right) + \cdots

Each group exceeds 12\frac{1}{2}: 13+14>14+14=12\frac{1}{3} + \frac{1}{4} \gt \frac{1}{4} + \frac{1}{4} = \frac{1}{2}And so on. Since we can Form infinitely many groups each exceeding 12\frac{1}{2}The partial sums diverge to ++\infty.

Geometric Series (CED BC Unit 10.2)

n=0arn=a1r,r<1\sum_{n=0}^{\infty} ar^n = \frac{a}{1 - r}, \quad |r| \lt 1

The series diverges when r1|r| \ge 1.

Derivation. The nnTh partial sum is Sn=a+ar+ar2++arn1S_n = a + ar + ar^2 + \cdots + ar^{n-1}. Then:

RSn=ar+ar2++arnRS_n = ar + ar^2 + \cdots + ar^n SnrSn=aarn    Sn(1r)=a(1rn)S_n - rS_n = a - ar^n \implies S_n(1 - r) = a(1 - r^n) Sn=a(1rn)1rS_n = \frac{a(1 - r^n)}{1 - r}

When r<1|r| \lt 1, rn0r^n \to 0So Sna1rS_n \to \frac{a}{1 - r}.

Example

Evaluate n=132n\displaystyle\sum_{n=1}^{\infty} \frac{3}{2^n}.

Rewrite as n=13(12)n\displaystyle\sum_{n=1}^{\infty} 3\left(\frac{1}{2}\right)^n. Here a=32a = \frac{3}{2} And r=12r = \frac{1}{2}.

n=132n=3/211/2=3/21/2=3\sum_{n=1}^{\infty} \frac{3}{2^n} = \frac{3/2}{1 - 1/2} = \frac{3/2}{1/2} = 3

Repeating Decimals as Geometric Series

Every repeating decimal can be expressed as a rational number using geometric series.

Example

Express 0.370.\overline{37} as a fraction.

0.37=37100+3710000+371000000+=n=137100n0.\overline{37} = \frac{37}{100} + \frac{37}{10000} + \frac{37}{1000000} + \cdots = \sum_{n=1}^{\infty} \frac{37}{100^n}

This is a geometric series with a=37100a = \frac{37}{100} and r=1100r = \frac{1}{100}.

0.37=37/10011/100=37/10099/100=37990.\overline{37} = \frac{37/100}{1 - 1/100} = \frac{37/100}{99/100} = \frac{37}{99}

Telescoping Series

A telescoping series has terms that cancel in pairs when the partial sum is expanded.

Example

Evaluate n=11n(n+1)\displaystyle\sum_{n=1}^{\infty} \frac{1}{n(n+1)}.

Use partial fractions: 1n(n+1)=1n1n+1\displaystyle\frac{1}{n(n+1)} = \frac{1}{n} - \frac{1}{n+1}.

Sn=(112)+(1213)++(1n1n+1)=11n+1S_n = \left(1 - \frac{1}{2}\right) + \left(\frac{1}{2} - \frac{1}{3}\right) + \cdots + \left(\frac{1}{n} - \frac{1}{n+1}\right) = 1 - \frac{1}{n+1}limnSn=1\lim_{n \to \infty} S_n = 1

Worked Example: Telescoping with Partial Fractions

Evaluate n=21n21\displaystyle\sum_{n=2}^{\infty} \frac{1}{n^2 - 1}.

Factor: 1n21=1(n1)(n+1)\frac{1}{n^2-1} = \frac{1}{(n-1)(n+1)}. By partial fractions: 1(n1)(n+1)=12 ⁣(1n11n+1)\frac{1}{(n-1)(n+1)} = \frac{1}{2}\!\left(\frac{1}{n-1} - \frac{1}{n+1}\right).

SN=12[(1113)+(1214)+(1315)++(1N11N+1)]S_N = \frac{1}{2}\left[\left(\frac{1}{1} - \frac{1}{3}\right) + \left(\frac{1}{2} - \frac{1}{4}\right) + \left(\frac{1}{3} - \frac{1}{5}\right) + \cdots + \left(\frac{1}{N-1} - \frac{1}{N+1}\right)\right]

Most terms cancel, leaving:

SN=12(1+121N1N+1)S_N = \frac{1}{2}\left(1 + \frac{1}{2} - \frac{1}{N} - \frac{1}{N+1}\right) limNSN=12(32)=34\lim_{N \to \infty} S_N = \frac{1}{2}\left(\frac{3}{2}\right) = \frac{3}{4}

The Integral Test (CED BC Unit 10.3)

If ff is continuous, positive, and decreasing on [1,)[1, \infty)And an=f(n)a_n = f(n)Then:

\sum_{n=1}^{\infty} a_n \quad \mathrm{and \quad \int_1^{\infty} f(x)\, dx

Either both converge or both diverge.

Why it works. The sum n=2f(n)\sum_{n=2}^{\infty} f(n) can be bounded by the integral:

1f(x)dxn=1f(n)f(1)+1f(x)dx\int_1^{\infty} f(x)\, dx \le \sum_{n=1}^{\infty} f(n) \le f(1) + \int_1^{\infty} f(x)\, dx

So if the integral converges, the sum is bounded above and (since terms are positive) must converge. If the integral diverges, the sum exceeds any bound and must diverge.

Remainder Estimate for the Integral Test

If an\sum a_n converges by the integral test and Rn=SSnR_n = S - S_n is the remainder after nn terms:

n+1f(x)dxRnnf(x)dx\int_{n+1}^{\infty} f(x)\, dx \le R_n \le \int_n^{\infty} f(x)\, dx

pp-Series

n=11np\sum_{n=1}^{\infty} \frac{1}{n^p}
  • Converges if p>1p \gt 1
  • Diverges if p1p \le 1

This follows directly from the integral test: 1dxxp\int_1^{\infty} \frac{dx}{x^p} converges if and only If p>1p \gt 1.

The pp-series with p=1p = 1 is the harmonic series, which diverges. This is the “boundary case” that Separates convergence from divergence.

Comparison Tests (CED BC Unit 10.5)

Direct Comparison Test

Suppose 0anbn0 \le a_n \le b_n for all nn (eventually):

  • If bn\sum b_n converges, then an\sum a_n converges.
  • If an\sum a_n diverges, then bn\sum b_n diverges.

Intuition: If a larger sum converges, the smaller one must too. If a smaller sum diverges, the Larger one must too.

Limit Comparison Test

Suppose an>0a_n \gt 0 and bn>0b_n \gt 0 for all nnAnd:

L=limnanbnL = \lim_{n \to \infty} \frac{a_n}{b_n}
  • If 0<L<0 \lt L \lt \inftyThen an\sum a_n and bn\sum b_n either both converge or both diverge.
  • If L=0L = 0 and bn\sum b_n converges, then an\sum a_n converges.
  • If L=L = \infty and bn\sum b_n diverges, then an\sum a_n diverges.

The case 0<L<0 \lt L \lt \infty is the most commonly used: it says the two series have the “same order Of magnitude,” so they share the same convergence behavior.

Example

Determine whether n=11n2+1\displaystyle\sum_{n=1}^{\infty} \frac{1}{n^2 + 1} converges.

Compare with 1n2\displaystyle\sum \frac{1}{n^2} (a convergent pp-series with p=2p = 2):

limn1/(n2+1)1/n2=limnn2n2+1=1\lim_{n \to \infty} \frac{1/(n^2+1)}{1/n^2} = \lim_{n \to \infty} \frac{n^2}{n^2 + 1} = 1

Since 0<1<0 \lt 1 \lt \inftyBoth series converge by the limit comparison test.

Worked Example: Choosing the Right Comparison

Determine whether n=13n+1n32\displaystyle\sum_{n=1}^{\infty} \frac{3n + 1}{n^3 - 2} converges.

For large nn, 3n+1n323nn3=3n2\frac{3n+1}{n^3-2} \approx \frac{3n}{n^3} = \frac{3}{n^2}.

Compare with 1n2\sum \frac{1}{n^2}:

limn(3n+1)/(n32)1/n2=limnn2(3n+1)n32=limn3n3+n2n32=3\lim_{n \to \infty} \frac{(3n+1)/(n^3-2)}{1/n^2} = \lim_{n \to \infty} \frac{n^2(3n+1)}{n^3-2} = \lim_{n \to \infty} \frac{3n^3 + n^2}{n^3 - 2} = 3

Since L=3(0,)L = 3 \in (0, \infty)Both series converge.

The Ratio Test (CED BC Unit 10.7)

For an\displaystyle\sum a_nCompute:

L=limnan+1anL = \lim_{n \to \infty} \left|\frac{a_{n+1}}{a_n}\right|
  • If L<1L \lt 1: the series converges absolutely.
  • If L>1L \gt 1 (or L=L = \infty): the series diverges.
  • If L=1L = 1: the test is inconclusive.

The ratio test is especially useful when the terms involve factorials or exponentials, because the Ratio tends to simplify dramatically.

Why it connects to geometric series. If an+1anL<1\left|\frac{a_{n+1}}{a_n}\right| \to L \lt 1Then for Large nn the terms behave like a geometric series with ratio LLAnd geometric series converge When the ratio is less than 1.

Example

Determine whether n=1n!10n\displaystyle\sum_{n=1}^{\infty} \frac{n!}{10^n} converges.

L=limn(n+1)!/10n+1n!/10n=limnn+110=L = \lim_{n \to \infty} \frac{(n+1)! / 10^{n+1}}{n! / 10^n} = \lim_{n \to \infty} \frac{n+1}{10} = \infty

Since L=>1L = \infty \gt 1The series diverges.

Example

Determine whether n=12nn!\displaystyle\sum_{n=1}^{\infty} \frac{2^n}{n!} converges.

L=limn2n+1/(n+1)!2n/n!=limn2n+1=0L = \lim_{n \to \infty} \frac{2^{n+1} / (n+1)!}{2^n / n!} = \lim_{n \to \infty} \frac{2}{n+1} = 0

Since L=0<1L = 0 \lt 1The series converges absolutely.

The Alternating Series Test (Leibniz Test)

If {an}\{a_n\} is a sequence that satisfies:

  1. an>0a_n \gt 0 for all nn (eventually),
  2. an+1ana_{n+1} \le a_n for all nn (eventually) — the terms decrease, and
  3. limnan=0\displaystyle\lim_{n \to \infty} a_n = 0

Then the alternating series n=1(1)n1an\displaystyle\sum_{n=1}^{\infty} (-1)^{n-1} a_n converges.

Intuition: The partial sums oscillate, but the oscillations shrink because the terms decrease. The odd-indexed partial sums S1,S3,S5,S_1, S_3, S_5, \ldots form a decreasing sequence bounded below, and The even-indexed partial sums S2,S4,S6,S_2, S_4, S_6, \ldots form an increasing sequence bounded above. Both converge to the same limit.

Alternating Series Estimation Theorem

If S=n=1(1)n1anS = \displaystyle\sum_{n=1}^{\infty} (-1)^{n-1} a_n is a convergent alternating series, then The error in using SnS_n to approximate SS satisfies:

Rn=SSnan+1|R_n| = |S - S_n| \le a_{n+1}

That is, the error is bounded by the first omitted term. This is remarkably useful: you can control The error by counting terms.

Example

How many terms of n=1(1)n1n\displaystyle\sum_{n=1}^{\infty} \frac{(-1)^{n-1}}{n} are needed to approximate The sum with error less than 0.0010.001?

The terms are an=1na_n = \frac{1}{n}Which decrease and approach 0.

We need an+1=1n+1<0.001a_{n+1} = \frac{1}{n+1} \lt 0.001So n+1>1000n + 1 \gt 1000Meaning n1000n \ge 1000.

At least 1000 terms are needed.

Absolute and Conditional Convergence

  • Absolutely convergent: an\displaystyle\sum |a_n| converges.
  • Conditionally convergent: an\displaystyle\sum a_n converges but an\displaystyle\sum |a_n| diverges.

Theorem. If a series converges absolutely, it converges.

Proof sketch. ananan-|a_n| \le a_n \le |a_n|So 0an+an2an0 \le a_n + |a_n| \le 2|a_n|. Since 2an\sum 2|a_n| Converges, (an+an)\sum (a_n + |a_n|) converges by the comparison test. Therefore an=(an+an)an\sum a_n = \sum (a_n + |a_n|) - \sum |a_n| converges as the difference of two convergent series.

Riemann rearrangement theorem. A conditionally convergent series can be rearranged to converge To any real number, or to diverge. This is not true for absolutely convergent series, whose sum is Invariant under rearrangement.

Example

Classify n=1(1)nn\displaystyle\sum_{n=1}^{\infty} \frac{(-1)^n}{n}.

The alternating series converges by the alternating series test.

Check absolute convergence: n=11n\displaystyle\sum_{n=1}^{\infty} \frac{1}{n} is the harmonic series, Which diverges.

Therefore, the series converges conditionally.

Power Series (CED BC Unit 10.8)

A power series centered at aa is:

n=0cn(xa)n=c0+c1(xa)+c2(xa)2+\sum_{n=0}^{\infty} c_n(x - a)^n = c_0 + c_1(x-a) + c_2(x-a)^2 + \cdots

A power series is a “polynomial with infinitely many terms.” The central question for any power Series is: for which values of xx does it converge?

Interval and Radius of Convergence

Every power series converges in an interval (aR,a+R)(a - R, a + R) where RR is the radius of Convergence:

  • Use the ratio test to find RR: R=1limncn+1/cn\displaystyle R = \frac{1}{\lim_{n \to \infty} |c_{n+1}/c_n|}.
  • Check the endpoints separately (the ratio test is inconclusive when L=1L = 1).
CaseInterval of Convergence
R=0R = 0Single point {a}\{a\}
R=R = \infty(,)(-\infty, \infty)
0<R<0 \lt R \lt \inftyCheck endpoints of (aR,a+R)(a - R, a + R)

Example

Find the interval of convergence for n=0(x2)nn!\displaystyle\sum_{n=0}^{\infty} \frac{(x - 2)^n}{n!}.

Apply the ratio test:

L=limn(x2)n+1/(n+1)!(x2)n/n!=limnx2n+1=0L = \lim_{n \to \infty} \left|\frac{(x-2)^{n+1}/(n+1)!}{(x-2)^n/n!}\right| = \lim_{n \to \infty} \frac{|x-2|}{n+1} = 0

Since L=0<1L = 0 \lt 1 for all xxThe series converges for all real numbers. The interval of Convergence is (,)(-\infty, \infty) with R=R = \infty.

Example

Find the interval of convergence for n=1(x1)nn\displaystyle\sum_{n=1}^{\infty} \frac{(x-1)^n}{n}.

L=limn(x1)n+1/(n+1)(x1)n/n=x1limnnn+1=x1L = \lim_{n \to \infty} \left|\frac{(x-1)^{n+1}/(n+1)}{(x-1)^n/n}\right| = |x - 1| \cdot \lim_{n \to \infty} \frac{n}{n+1} = |x - 1|

Converges when x1<1|x - 1| \lt 1I.e., 0<x<20 \lt x \lt 2. Radius R=1R = 1.

Check x=0x = 0: n=1(1)nn\displaystyle\sum_{n=1}^{\infty} \frac{(-1)^n}{n} converges (alternating Series).

Check x=2x = 2: n=11n\displaystyle\sum_{n=1}^{\infty} \frac{1}{n} diverges (harmonic series).

Interval of convergence: [0,2)[0, 2).

Term-by-Term Differentiation and Integration

If f(x)=n=0cn(xa)n\displaystyle f(x) = \sum_{n=0}^{\infty} c_n(x-a)^n with radius RRThen:

F'(x) = \sum_{n=1}^{\infty} n c_n (x-a)^{n-1}, \quad \mathrm{same radius R \int f(x)\, dx = C + \sum_{n=0}^{\infty} \frac{c_n (x-a)^{n+1}}{n+1}, \quad \mathrm{same radius R

Differentiation and integration of power series do not change the radius of convergence (though the Behaviour at the endpoints may change).

Taylor and Maclaurin Series (CED BC Unit 10.11)

The Taylor series of ff centered at aa is:

F(x)=n=0f(n)(a)n!(xa)nF(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(a)}{n!}(x - a)^n

When a=0a = 0This is called a Maclaurin series.

Why Taylor Series Work

The Taylor polynomial Tn(x)=k=0nf(k)(a)k!(xa)kT_n(x) = \sum_{k=0}^{n} \frac{f^{(k)}(a)}{k!}(x-a)^k is the unique Polynomial of degree n\le n whose value and first nn derivatives at x=ax = a match those of ff. As nn \to \inftyIf the remainder Rn(x)=f(x)Tn(x)0R_n(x) = f(x) - T_n(x) \to 0Then the Taylor series converges to f(x)f(x).

Common Maclaurin Series

Ex=n=0xnn!=1+x+x22!+x33!+,R=E^x = \sum_{n=0}^{\infty} \frac{x^n}{n!} = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + \cdots, \quad R = \infty sinx=n=0(1)nx2n+1(2n+1)!=xx33!+x55!,R=\sin x = \sum_{n=0}^{\infty} \frac{(-1)^n x^{2n+1}}{(2n+1)!} = x - \frac{x^3}{3!} + \frac{x^5}{5!} - \cdots, \quad R = \infty cosx=n=0(1)nx2n(2n)!=1x22!+x44!,R=\cos x = \sum_{n=0}^{\infty} \frac{(-1)^n x^{2n}}{(2n)!} = 1 - \frac{x^2}{2!} + \frac{x^4}{4!} - \cdots, \quad R = \infty 11x=n=0xn=1+x+x2+x3+,R=1\frac{1}{1-x} = \sum_{n=0}^{\infty} x^n = 1 + x + x^2 + x^3 + \cdots, \quad R = 1 ln(1+x)=n=1(1)n1xnn=xx22+x33,R=1\ln(1+x) = \sum_{n=1}^{\infty} \frac{(-1)^{n-1}x^n}{n} = x - \frac{x^2}{2} + \frac{x^3}{3} - \cdots, \quad R = 1 (1+x)k=n=0(kn)xn,R=1(1+x)^k = \sum_{n=0}^{\infty} \binom{k}{n} x^n, \quad R = 1 arctanx=n=0(1)nx2n+12n+1=xx33+x55,R=1\arctan x = \sum_{n=0}^{\infty} \frac{(-1)^n x^{2n+1}}{2n+1} = x - \frac{x^3}{3} + \frac{x^5}{5} - \cdots, \quad R = 1

Taylor’s Inequality (Remainder Estimation)

The remainder after nn terms of the Taylor series satisfies:

Rn(x)Mxan+1(n+1)!|R_n(x)| \le \frac{M|x - a|^{n+1}}{(n+1)!}

Where MM is an upper bound for f(n+1)(z)|f^{(n+1)}(z)| for zz between aa and xx.

Example

Use the Maclaurin series for exe^x to approximate e0.1e^{0.1} with error less than 10810^{-8}.

E0.1=n=0N(0.1)nn!+RNE^{0.1} = \sum_{n=0}^{N} \frac{(0.1)^n}{n!} + R_N

We need RNM(0.1)N+1(N+1)!<108|R_N| \le \frac{M \cdot (0.1)^{N+1}}{(N+1)!} \lt 10^{-8}.

Since f(n+1)(x)=exe0.1<1.2f^{(n+1)}(x) = e^x \le e^{0.1} \lt 1.2 for x[0,0.1]x \in [0, 0.1]:

1.2(0.1)N+1(N+1)!<108\frac{1.2 \cdot (0.1)^{N+1}}{(N+1)!} \lt 10^{-8}

For N=3N = 3: 1.210424=5×106\displaystyle\frac{1.2 \cdot 10^{-4}}{24} = 5 \times 10^{-6} (too large).

For N=5N = 5: 1.21067201.67×109<108\displaystyle\frac{1.2 \cdot 10^{-6}}{720} \approx 1.67 \times 10^{-9} \lt 10^{-8}.

So using 6 terms (up to n=5n = 5):

E0.11+0.1+0.012+0.0016+10424+1051201.1051708E^{0.1} \approx 1 + 0.1 + \frac{0.01}{2} + \frac{0.001}{6} + \frac{10^{-4}}{24} + \frac{10^{-5}}{120} \approx 1.1051708

Deriving Maclaurin Series by Substitution

You do not need to compute derivatives from scratch every time. If you know the series for eue^u You can substitute u=x2u = -x^2 to get the series for ex2e^{-x^2}.

Example

Find the Maclaurin series for cos(x2)\cos(x^2).

Substitute u=x2u = x^2 into the series for cosu\cos u:

cos(x2)=n=0(1)n(x2)2n(2n)!=n=0(1)nx4n(2n)!=1x42!+x84!\cos(x^2) = \sum_{n=0}^{\infty} \frac{(-1)^n (x^2)^{2n}}{(2n)!} = \sum_{n=0}^{\infty} \frac{(-1)^n x^{4n}}{(2n)!} = 1 - \frac{x^4}{2!} + \frac{x^8}{4!} - \cdots

Operations on Power Series

Multiplication of Power Series

If anxn\sum a_n x^n and bnxn\sum b_n x^n both have radius RRThen their Cauchy product also has radius RR:

(n=0anxn) ⁣(n=0bnxn)=n=0cnxn\left(\sum_{n=0}^{\infty} a_n x^n\right)\!\left(\sum_{n=0}^{\infty} b_n x^n\right) = \sum_{n=0}^{\infty} c_n x^n

Where cn=k=0nakbnkc_n = \sum_{k=0}^{n} a_k b_{n-k}.

Example

Find the Maclaurin series for exsinxe^x \sin x up to the x5x^5 term.

Ex=1+x+x22+x36+x424+E^x = 1 + x + \frac{x^2}{2} + \frac{x^3}{6} + \frac{x^4}{24} + \cdotssinx=xx36+x5120\sin x = x - \frac{x^3}{6} + \frac{x^5}{120} - \cdots

Multiplying and collecting terms up to x5x^5:

Exsinx=x+x2+x33x530+E^x \sin x = x + x^2 + \frac{x^3}{3} - \frac{x^5}{30} + \cdots

Integration of Power Series

Example

Find the Maclaurin series for ln(1+x)\ln(1 + x) by integrating the geometric series.

11(x)=n=0(x)n=n=0(1)nxn,x<1\frac{1}{1 - (-x)} = \sum_{n=0}^{\infty} (-x)^n = \sum_{n=0}^{\infty} (-1)^n x^n, \quad |x| \lt 1

Integrate term by term:

0x11+tdt=n=0(1)n0xtndt=n=0(1)nxn+1n+1\int_0^x \frac{1}{1 + t}\, dt = \sum_{n=0}^{\infty} (-1)^n \int_0^x t^n\, dt = \sum_{n=0}^{\infty} \frac{(-1)^n x^{n+1}}{n+1}ln(1+x)=n=0(1)nxn+1n+1=n=1(1)n1xnn,x<1\ln(1 + x) = \sum_{n=0}^{\infty} \frac{(-1)^n x^{n+1}}{n+1} = \sum_{n=1}^{\infty} \frac{(-1)^{n-1} x^n}{n}, \quad |x| \lt 1

Common Pitfalls

  1. Confusing sequences and series. A sequence is a list; a series is a sum. A convergent sequence does not imply a convergent series (e.g., an=1na_n = \frac{1}{n} converges to 0, but 1n\sum \frac{1}{n} diverges).

  2. Using the nnTh-term test incorrectly. liman=0\lim a_n = 0 does not prove convergence (e.g., harmonic series). The test only detects divergence.

  3. Forgetting to check endpoints of the interval of convergence for power series. The ratio test always gives L=1L = 1 at the endpoints, so you must use a different test.

  4. Misidentifying the center of a Taylor series. For cn(x3)n\sum c_n(x - 3)^nThe center is a=3a = 3.

  5. Applying the ratio test when L=1L = 1. The test is inconclusive; use a different test (comparison, integral, alternating series).

  6. Confusing absolute and conditional convergence. An alternating harmonic series converges conditionally, not absolutely. Only absolutely convergent series can be freely rearranged.

  7. Computing Taylor series coefficients incorrectly. Always use cn=f(n)(a)n!c_n = \frac{f^{(n)}(a)}{n!} not just f(n)(a)f^{(n)}(a). Forgetting to divide by n!n! is a common mistake.

  8. Assuming convergence at endpoints. The interval of convergence may be open, closed, or half-open at each endpoint. You must test each one individually.

Practice Questions

  1. Determine whether n=12nn!\displaystyle\sum_{n=1}^{\infty} \frac{2^n}{n!} converges or diverges.

  2. Find the interval of convergence for n=0(1)nxn3n\displaystyle\sum_{n=0}^{\infty} \frac{(-1)^n x^n}{3^n}.

  3. Find the Maclaurin series for f(x)=xexf(x) = x e^x.

  4. How many terms of n=1(1)nn2\displaystyle\sum_{n=1}^{\infty} \frac{(-1)^n}{n^2} are needed to approximate the sum with error less than 0.010.01?

  5. Use the limit comparison test to determine whether n=152n23n+1\displaystyle\sum_{n=1}^{\infty} \frac{5}{2n^2 - 3n + 1} converges.

  6. Find the Taylor series for lnx\ln x centered at a=1a = 1 and determine its radius of convergence.

  7. Find the Maclaurin series for arctanx\arctan x by integrating the geometric series.

  8. Use the Maclaurin series for cosx\cos x to approximate cos(0.2)\cos(0.2) with error less than 10610^{-6}.

  9. Determine whether n=1nen\displaystyle\sum_{n=1}^{\infty} \frac{n}{e^n} converges using the ratio test.

  10. Find the Maclaurin series for x1x2\frac{x}{1-x^2} and determine its interval of convergence.

  11. Express 0.2710.\overline{271} as a fraction using geometric series.

  12. Use the alternating series estimation theorem to bound the error in approximating n=1(1)nn3\displaystyle\sum_{n=1}^{\infty} \frac{(-1)^n}{n^3} by its first 10 terms.

Practice Problems

Question 1: Taylor series expansion

Find the first four nonzero terms of the Maclaurin series for f(x)=ln(1+x)f(x) = \ln(1 + x) and use it to approximate ln(1.1)\ln(1.1).

Answer

f(0)=ln(1)=0f(0) = \ln(1) = 0.

f(x)=11+xf'(x) = \frac{1}{1+x}, f(0)=1f'(0) = 1.

f(x)=1(1+x)2f''(x) = \frac{-1}{(1+x)^2}, f(0)=1f''(0) = -1.

f(x)=2(1+x)3f'''(x) = \frac{2}{(1+x)^3}, f(0)=2f'''(0) = 2.

f(4)(x)=6(1+x)4f^{(4)}(x) = \frac{-6}{(1+x)^4}, f(4)(0)=6f^{(4)}(0) = -6.

Maclaurin series: ln(1+x)=xx22+x33x44+\ln(1+x) = x - \frac{x^2}{2} + \frac{x^3}{3} - \frac{x^4}{4} + \cdots

For ln(1.1)\ln(1.1) with x=0.1x = 0.1: ln(1.1)0.10.005+0.0003330.000025=0.095308\ln(1.1) \approx 0.1 - 0.005 + 0.000333 - 0.000025 = 0.095308.

Actual: ln(1.1)0.09531\ln(1.1) \approx 0.09531. The approximation is accurate to 5 decimal places.

Question 2: Ratio test

Determine the radius of convergence of n=0(2x)nn!\displaystyle\sum_{n=0}^{\infty} \frac{(2x)^n}{n!}.

Answer

an=2nxnn!a_n = \frac{2^n x^n}{n!}.

L=limnan+1an=limn2n+1xn+1/(n+1)!2nxn/n!=limn2xn+1=0\displaystyle L = \lim_{n \to \infty} \left|\frac{a_{n+1}}{a_n}\right| = \lim_{n \to \infty} \left|\frac{2^{n+1} x^{n+1} / (n+1)!}{2^n x^n / n!}\right| = \lim_{n \to \infty} \frac{2|x|}{n+1} = 0.

Since L=0<1L = 0 \lt 1 for all xxThe radius of convergence is R=R = \infty. The series converges for all real xx. (This is the Maclaurin series for e2xe^{2x}.)

Question 3: Alternating series

Determine whether n=1(1)n+1n\displaystyle\sum_{n=1}^{\infty} \frac{(-1)^{n+1}}{\sqrt{n}} converges absolutely, converges conditionally, or diverges.

Answer

Alternating series test: an=1na_n = \frac{1}{\sqrt{n}} is positive, decreasing, and limn1n=0\lim_{n \to \infty} \frac{1}{\sqrt{n}} = 0. The alternating series converges.

Absolute convergence: 1n\sum \frac{1}{\sqrt{n}} is a p-series with p=1/2<1p = 1/2 \lt 1So it diverges.

Therefore, the series converges conditionally (but not absolutely).

Question 4: Power series representation

Find the power series representation for 1(1x)2\displaystyle\frac{1}{(1-x)^2} and determine its interval of convergence.

Answer

We know 11x=n=0xn\frac{1}{1-x} = \sum_{n=0}^{\infty} x^n for x<1|x| \lt 1.

Differentiate both sides: 1(1x)2=n=1nxn1=n=0(n+1)xn\frac{1}{(1-x)^2} = \sum_{n=1}^{\infty} nx^{n-1} = \sum_{n=0}^{\infty} (n+1)x^n.

Interval of convergence: x<1|x| \lt 1Or (1,1)(-1, 1).

Check endpoints: at x=1x = 1Series is (n+1)\sum (n+1) which diverges. At x=1x = -1Series is (1)n(n+1)\sum (-1)^n(n+1) which diverges by the divergence test.

Question 5: Telescoping series

Evaluate n=11n(n+1)\displaystyle\sum_{n=1}^{\infty} \frac{1}{n(n+1)}.

Answer

Partial fraction decomposition: 1n(n+1)=1n1n+1\frac{1}{n(n+1)} = \frac{1}{n} - \frac{1}{n+1}.

SN=n=1N(1n1n+1)=112+1213+131N+1S_N = \sum_{n=1}^{N} \left(\frac{1}{n} - \frac{1}{n+1}\right) = 1 - \frac{1}{2} + \frac{1}{2} - \frac{1}{3} + \frac{1}{3} - \cdots - \frac{1}{N+1}.

All intermediate terms cancel (telescoping): SN=11N+1S_N = 1 - \frac{1}{N+1}.

n=11n(n+1)=limN(11N+1)=1\displaystyle\sum_{n=1}^{\infty} \frac{1}{n(n+1)} = \lim_{N \to \infty} \left(1 - \frac{1}{N+1}\right) = 1.


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Summary

This topic covers the mathematical techniques and concepts related to sequences and series, including key theorems, methods, and problem-solving approaches.

Key concepts include:

  • arithmetic and geometric sequences
  • series and sigma notation
  • recurrence relations
  • convergence tests
  • mathematical induction

Regular practice with a variety of question types is essential to build fluency and confidence in applying these mathematical techniques.

Worked Examples

Worked examples demonstrating the application of key concepts are covered in the detailed sub-pages linked above.