A sequence is an ordered list of numbers: a1,a2,a3,…. Formally, a sequence is a
Function from the positive integers (or a subset thereof) to the real numbers:
a:N→RWritten as {an}n=1∞ or {an}.
A sequence {an}converges to a limit L if:
n→∞liman=L
This means: for every ϵ>0There exists an integer N such that ∣an−L∣<ϵ
for all n≥N. The terms eventually get and stay arbitrarily close to L.
If no such limit exists, the sequence diverges.
Bounded and Monotone Sequences
Bounded above:an≤M for all n and some M.
Bounded below:an≥m for all n and some m.
Bounded: bounded both above and below.
Monotone increasing:an+1≥an for all n.
Monotone decreasing:an+1≤an for all n.
Eventually monotone: the monotonicity holds for all n beyond some index N.
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 +∞. A
Monotone decreasing sequence that is not bounded below diverges to −∞.
Since lnn grows slower than any positive power of nWe have lnn<n for
Sufficiently large n. Therefore
0<nlnn<nn=n1And n1→0 So
by the squeeze theorem, nlnn→0.
Series (CED BC Unit 10)
An infinite series is the sum of the terms of an infinite sequence:
n=1∑∞an=a1+a2+a3+⋯
Partial Sums
The nTh partial sum is Sn=∑k=1nak. The series converges if and only if the
Sequence of partial sums {Sn} converges:
n=1∑∞an=L⟺n→∞limSn=L
If {Sn} diverges, the series diverges.
The nTh-Term Test (Divergence Test)
If n→∞liman=0Then ∑an diverges.
Proof (by contrapositive): If ∑an converges to LThen Sn→L and Sn−1→L.
Since an=Sn−Sn−1We get an→L−L=0.
Caution: If n→∞liman=0The test is inconclusive. The series may
Converge or diverge. The harmonic series ∑n1 is the canonical counterexample.
Example
Does n=1∑∞n+1n converge?
n→∞limn+1n=1=0
By the nTh-term test, the series diverges.
The Harmonic Series
n=1∑∞n1=1+21+31+41+⋯
Even though n1→0This series diverges. The proof groups terms:
1+21+(31+41)+(51+61+71+81)+⋯
Each group exceeds 21:
31+41>41+41=21And so on. Since we can Form
infinitely many groups each exceeding 21The partial sums diverge to +∞.
Geometric Series (CED BC Unit 10.2)
n=0∑∞arn=1−ra,∣r∣<1
The series diverges when ∣r∣≥1.
Derivation. The nTh partial sum is Sn=a+ar+ar2+⋯+arn−1. Then:
Why it works. The sum ∑n=2∞f(n) can be bounded by the integral:
∫1∞f(x)dx≤n=1∑∞f(n)≤f(1)+∫1∞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 converges by the integral test and Rn=S−Sn is the remainder after n terms:
∫n+1∞f(x)dx≤Rn≤∫n∞f(x)dx
p-Series
n=1∑∞np1
Converges if p>1
Diverges if p≤1
This follows directly from the integral test: ∫1∞xpdx converges if and only
If p>1.
The p-series with p=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 0≤an≤bn for all n (eventually):
If ∑bn converges, then ∑an converges.
If ∑an diverges, then ∑bn 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>0 and bn>0 for all nAnd:
L=n→∞limbnan
If 0<L<∞Then ∑an and ∑bn either both converge or both diverge.
If L=0 and ∑bn converges, then ∑an converges.
If L=∞ and ∑bn diverges, then ∑an diverges.
The case 0<L<∞ 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=1∑∞n2+11 converges.
Compare with ∑n21 (a convergent p-series with p=2):
n→∞lim1/n21/(n2+1)=n→∞limn2+1n2=1
Since 0<1<∞Both series converge by the limit comparison test.
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 anan+1→L<1Then for
Large n the terms behave like a geometric series with ratio LAnd geometric series converge When
the ratio is less than 1.
Example
Determine whether n=1∑∞10nn! converges.
L=n→∞limn!/10n(n+1)!/10n+1=n→∞lim10n+1=∞
Since L=∞>1The series diverges.
Example
Determine whether n=1∑∞n!2n converges.
L=n→∞lim2n/n!2n+1/(n+1)!=n→∞limn+12=0
Since L=0<1The series converges absolutely.
The Alternating Series Test (Leibniz Test)
If {an} is a sequence that satisfies:
an>0 for all n (eventually),
an+1≤an for all n (eventually) — the terms decrease, and
n→∞liman=0
Then the alternating series n=1∑∞(−1)n−1an converges.
Intuition: The partial sums oscillate, but the oscillations shrink because the terms decrease.
The odd-indexed partial sums S1,S3,S5,… form a decreasing sequence bounded below, and
The even-indexed partial sums S2,S4,S6,… form an increasing sequence bounded above.
Both converge to the same limit.
Alternating Series Estimation Theorem
If S=n=1∑∞(−1)n−1an is a convergent alternating series, then
The error in using Sn to approximate S satisfies:
∣Rn∣=∣S−Sn∣≤an+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∑∞n(−1)n−1 are needed to approximate
The sum with error less than 0.001?
The terms are an=n1Which decrease and approach 0.
We need an+1=n+11<0.001So n+1>1000Meaning n≥1000.
At least 1000 terms are needed.
Absolute and Conditional Convergence
Absolutely convergent:∑∣an∣ converges.
Conditionally convergent:∑an converges but ∑∣an∣
diverges.
Theorem. If a series converges absolutely, it converges.
Proof sketch.−∣an∣≤an≤∣an∣So 0≤an+∣an∣≤2∣an∣. Since ∑2∣an∣
Converges, ∑(an+∣an∣) converges by the comparison test. Therefore
∑an=∑(an+∣an∣)−∑∣an∣ 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∑∞n(−1)n.
The alternating series converges by the alternating series test.
Check absolute convergence: n=1∑∞n1 is the harmonic series,
Which diverges.
Therefore, the series converges conditionally.
Power Series (CED BC Unit 10.8)
A power series centered at a is:
n=0∑∞cn(x−a)n=c0+c1(x−a)+c2(x−a)2+⋯
A power series is a “polynomial with infinitely many terms.” The central question for any power
Series is: for which values of x does it converge?
Interval and Radius of Convergence
Every power series converges in an interval (a−R,a+R) where R is the radius of
Convergence:
Use the ratio test to find R: R=limn→∞∣cn+1/cn∣1.
Check the endpoints separately (the ratio test is inconclusive when L=1).
Case
Interval of Convergence
R=0
Single point {a}
R=∞
(−∞,∞)
0<R<∞
Check endpoints of (a−R,a+R)
Example
Find the interval of convergence for n=0∑∞n!(x−2)n.
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 f centered at a is:
F(x)=n=0∑∞n!f(n)(a)(x−a)n
When a=0This is called a Maclaurin series.
Why Taylor Series Work
The Taylor polynomial Tn(x)=∑k=0nk!f(k)(a)(x−a)k is the unique
Polynomial of degree ≤n whose value and first n derivatives at x=a match those of f. As
n→∞If the remainder Rn(x)=f(x)−Tn(x)→0Then the Taylor series converges to
f(x).
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=n1 converges to 0, but
∑n1 diverges).
Using the nTh-term test incorrectly.liman=0 does not prove convergence (e.g.,
harmonic series). The test only detects divergence.
Forgetting to check endpoints of the interval of convergence for power series. The ratio test
always gives L=1 at the endpoints, so you must use a different test.
Misidentifying the center of a Taylor series. For ∑cn(x−3)nThe center is a=3.
Applying the ratio test when L=1. The test is inconclusive; use a different test
(comparison, integral, alternating series).
Confusing absolute and conditional convergence. An alternating harmonic series converges
conditionally, not absolutely. Only absolutely convergent series can be freely rearranged.
Computing Taylor series coefficients incorrectly. Always use cn=n!f(n)(a)
not just f(n)(a). Forgetting to divide by n! is a common mistake.
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
Determine whether n=1∑∞n!2n converges or diverges.
Find the interval of convergence for n=0∑∞3n(−1)nxn.
Find the Maclaurin series for f(x)=xex.
How many terms of n=1∑∞n2(−1)n are needed to approximate
the sum with error less than 0.01?
Use the limit comparison test to determine whether
n=1∑∞2n2−3n+15 converges.
Find the Taylor series for lnx centered at a=1 and determine its radius of convergence.
Find the Maclaurin series for arctanx by integrating the geometric series.
Use the Maclaurin series for cosx to approximate cos(0.2) with error less than 10−6.
Determine whether n=1∑∞enn converges using the ratio
test.
Find the Maclaurin series for 1−x2x and determine its interval of convergence.
Express 0.271 as a fraction using geometric series.
Use the alternating series estimation theorem to bound the error in approximating
n=1∑∞n3(−1)n 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) and use it to
approximate ln(1.1).
Answer
f(0)=ln(1)=0.
f′(x)=1+x1, f′(0)=1.
f′′(x)=(1+x)2−1, f′′(0)=−1.
f′′′(x)=(1+x)32, f′′′(0)=2.
f(4)(x)=(1+x)4−6, f(4)(0)=−6.
Maclaurin series: ln(1+x)=x−2x2+3x3−4x4+⋯
For ln(1.1) with x=0.1: ln(1.1)≈0.1−0.005+0.000333−0.000025=0.095308.
Actual: ln(1.1)≈0.09531. The approximation is accurate to 5 decimal places.
Question 2: Ratio test
Determine the radius of convergence of n=0∑∞n!(2x)n.
All intermediate terms cancel (telescoping): SN=1−N+11.
n=1∑∞n(n+1)1=N→∞lim(1−N+11)=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.