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MATH
[1251]

Seen Questions

Worked solutions on Taylor polynomials, remainder bounds, sequences, convergence tests and power-series endpoints.

These past exam questions cover sequence limits and convergence tests, Taylor coefficients with a Lagrange remainder bound and the interval of convergence of a power series.

[DEFINITION]

Convergence of a sequence

The sequence {an}\{a_n\} converges to LL, written

lim⁡n→∞an=L,\lim_{n\to\infty}a_n=L,

if

∀ε>0 ∃N∈N such that n>N  ⟹  ∣an−L∣<ε.\forall\varepsilon>0\ \exists N\in\mathbb N \text{ such that }n>N\implies |a_n-L|<\varepsilon.
[THEOREM]

Monotone convergence theorem

A non-decreasing sequence bounded above converges. A non-increasing sequence bounded below converges.

[EXAMPLE]

Sequences and series

(a)

Let {an}n=0∞\{a_n\}_{n=0}^{\infty} be a sequence of non-negative real numbers. Which of the following ensures that {an}n=0∞\{a_n\}_{n=0}^{\infty} converges? Select all that apply.

  • {an}n=0∞\{a_n\}_{n=0}^{\infty} is bounded below and non-decreasing.
  • There exists L∈RL\in\mathbb R such that for each ε>0\varepsilon>0 there corresponds K∈NK\in\mathbb N such that ∣an−L∣<ε|a_n-L|<\varepsilon whenever n>Kn>K.
  • sup⁡{an:n∈N}\sup\{a_n:n\in\mathbb N\} exists.
  • {an}n=0∞\{a_n\}_{n=0}^{\infty} is bounded above and non-increasing.
  • inf⁡{an:n∈N}\inf\{a_n:n\in\mathbb N\} exists.

(b)

Consider the sequence {an}n=0∞\{a_n\}_{n=0}^{\infty} given by

a0=7,an+1=8−38−an(n≥0).a_0=7,\qquad a_{n+1}=8-\sqrt{38-a_n} \qquad(n\ge0).

Given that this sequence is decreasing and converges, find

L=lim⁡n→∞an.L=\lim_{n\to\infty}a_n.

(c)

Let {cn}n=0∞\{c_n\}_{n=0}^{\infty} and {dn}n=0∞\{d_n\}_{n=0}^{\infty} be sequences of strictly positive real numbers satisfying

lim⁡n→∞cn=L1<1,lim⁡n→∞dn=L2>1.\lim_{n\to\infty}c_n=L_1<1, \qquad \lim_{n\to\infty}d_n=L_2>1.

For n≥1n\ge1, define

bn=(cndn)n.b_n=\left(\frac{c_n}{d_n}\right)^n.

Determine which statements are true:

  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n is convergent by the integral test.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n is divergent by the ratio test.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n is divergent by the root test.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n is convergent by the ratio test.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n is convergent by the root test.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n is divergent by the integral test.

(d)

Let {an}n=0∞\{a_n\}_{n=0}^{\infty} and {bn}n=0∞\{b_n\}_{n=0}^{\infty} be sequences such that

an=2nα+O(n−α−1)as n→∞,a_n=\frac{2}{n^\alpha}+O(n^{-\alpha-1}) \qquad\text{as }n\to\infty,

and

bn=9nα+O(n−α−1)as n→∞,b_n=\frac{9}{n^\alpha}+O(n^{-\alpha-1}) \qquad\text{as }n\to\infty,

where α\alpha is a positive integer. Since these formulas describe only the tail, the associated series may be started at n=1n=1; finitely many initial terms do not affect convergence.

Determine which of the following statements hold:

  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n converges if and only if, ∑n=1∞an\displaystyle\sum_{n=1}^{\infty}a_n diverges.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n converges or diverges independently of whether ∑n=1∞an\displaystyle\sum_{n=1}^{\infty}a_n converges or not.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n converges if and only if, ∑n=1∞an\displaystyle\sum_{n=1}^{\infty}a_n converges.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n diverges if and only if, ∑n=1∞an\displaystyle\sum_{n=1}^{\infty}a_n converges.
  • ∑n=1∞bn\displaystyle\sum_{n=1}^{\infty}b_n diverges if and only if, ∑n=1∞an\displaystyle\sum_{n=1}^{\infty}a_n diverges.

Solution

(a)

The second statement is exactly the ε\varepsilon-NN definition of convergence, so it is sufficient.

The fourth statement is also sufficient. Being bounded above gives no lower bound, but the terms are non-negative, so an≥0a_n\ge0 supplies one and the Monotone Convergence Theorem gives convergence.

The other three statements are not sufficient:

  • a non-decreasing sequence that is only bounded below can be an=na_n=n;
  • a finite supremum does not prevent oscillation, as in an=0,1,0,1,…a_n=0,1,0,1,\ldots;
  • a finite infimum also does not prevent the same oscillation.

Therefore the correct selections are

the ε-N statement and the bounded-above, non-increasing statement.{\text{the $\varepsilon$-$N$ statement and the bounded-above, non-increasing statement}.}
(b)

Because the sequence converges and the square-root function is continuous on its domain, taking limits in the recurrence gives

L=8−38−L.L=8-\sqrt{38-L}.

Before squaring, observe that

38−L=8−L≥0,\sqrt{38-L}=8-L\ge0,

so any admissible limit must satisfy L≤8L\le8. Squaring now gives

38−L=(8−L)2=64−16L+L2,\begin{aligned} 38-L&=(8-L)^2\\ &=64-16L+L^2, \end{aligned}

and hence

L2−15L+26=0⟺(L−2)(L−13)=0.L^2-15L+26=0 \quad\Longleftrightarrow\quad (L-2)(L-13)=0.

The algebraic candidates are L=2L=2 and L=13L=13, but L=13L=13 violates the restriction L≤8L\le8 introduced before squaring. The remaining value checks in the original recurrence:

8−38−2=8−6=2.8-\sqrt{38-2}=8-6=2.

Therefore

L=2.{L=2}.
(c)

For n≥1n\ge1, the nnth root of bnb_n is

bnn=cndn,\sqrt[n]{b_n}=\frac{c_n}{d_n},

because cn,dn>0c_n,d_n>0. Therefore

lim⁡n→∞bnn=L1L2<1.\lim_{n\to\infty}\sqrt[n]{b_n} =\frac{L_1}{L_2}<1.

The root test proves convergence. The n=0n=0 term, if included, is just one finite initial term and has no effect on convergence. The given information does not determine the ratio-test limit or provide the smoothness and monotonicity needed for the integral test. Thus the only correct statement is

∑n=1∞bn is convergent by the root test.{\displaystyle\sum_{n=1}^{\infty}b_n \text{ is convergent by the root test}.}
(d)

The error terms are smaller than the displayed leading terms:

O(n−α−1)=o(n−α).O(n^{-\alpha-1})=o(n^{-\alpha}).

Consequently,

an∼2nα,bn∼9nα,a_n\sim\frac{2}{n^\alpha}, \qquad b_n\sim\frac{9}{n^\alpha},

so the terms are eventually positive. Their ratio satisfies

lim⁡n→∞bnan=lim⁡n→∞9n−α+O(n−α−1)2n−α+O(n−α−1)=92.\lim_{n\to\infty}\frac{b_n}{a_n} =\lim_{n\to\infty} \frac{9n^{-\alpha}+O(n^{-\alpha-1})} {2n^{-\alpha}+O(n^{-\alpha-1})} =\frac92.

Since this limit is finite and strictly positive, the Limit Comparison Test gives

∑bn converges⟺∑an converges.\sum b_n\text{ converges} \quad\Longleftrightarrow\quad \sum a_n\text{ converges}.

If α=1\alpha=1, both tails behave like the harmonic series and diverge; if α>1\alpha>1, both behave like a convergent pp-series. The correct selections are the third and fifth listed statements. The third is

∑n=1∞bn converges if and only if ∑n=1∞an converges.{\displaystyle \sum_{n=1}^{\infty}b_n\text{ converges if and only if } \sum_{n=1}^{\infty}a_n\text{ converges}.}

Taking logical complements gives the fifth:

∑n=1∞bn diverges if and only if ∑n=1∞an diverges.{\displaystyle \sum_{n=1}^{\infty}b_n\text{ diverges if and only if } \sum_{n=1}^{\infty}a_n\text{ diverges}.}

The sequence parts separate the definition of convergence from the sufficient conditions of monotonicity and boundedness. The series parts use the root test for exponential-type terms and limit comparison for matching power laws. In both, only the tail matters.

[DEFINITION]

Taylor polynomial

If ff has derivatives through order nn at aa, its Taylor polynomial of degree at most nn about aa is

Pn(x)=∑k=0nf(k)(a)k!(x−a)k.P_n(x)=\sum_{k=0}^{n}\frac{f^{(k)}(a)}{k!}(x-a)^k.
[METHOD]

Bound a Taylor approximation error

To prove that Pn(x)P_n(x) approximates f(x)f(x) within a tolerance ε\varepsilon:

  1. identify f(n+1)f^{(n+1)};
  2. find a bound MM for ∣f(n+1)(t)∣|f^{(n+1)}(t)| between aa and the relevant values of xx;
  3. use ∣f(x)−Pn(x)∣≤M∣x−a∣n+1(n+1)!;|f(x)-P_n(x)| \le \frac{M|x-a|^{n+1}}{(n+1)!};
  4. choose nn or the interval so that the right-hand side is at most ε\varepsilon.
[EXAMPLE]

Taylor polynomials and a Lagrange remainder

Aaron and Cindy are investigating a function f:R→Rf:\mathbb R\to\mathbb R and its first eight Taylor polynomials about x0=0.3x_0=0.3:

p0(x),p1(x),…,p7(x).p_0(x),p_1(x),\ldots,p_7(x).

Aaron compares the first six polynomials and records these features near x0x_0: p1p_1 is decreasing at x0x_0; p2=p1p_2=p_1; and, just to the right of x0x_0, p3−p2p_3-p_2 and p4−p3p_4-p_3 are positive, while p5−p4p_5-p_4 is negative. These observations replace the plots, which are not included here.

(a)

(i)

Select all derivatives of ff at 0.30.3 that are zero:

f′(0.3),f′′(0.3),f(3)(0.3),f(4)(0.3),f(5)(0.3).f'(0.3),\quad f''(0.3),\quad f^{(3)}(0.3),\quad f^{(4)}(0.3),\quad f^{(5)}(0.3).
(ii)

Select all derivatives of ff at 0.30.3 that are positive.

(iii)

Select all derivatives of ff at 0.30.3 that are negative.

(b)

Aaron tells Cindy that the coefficient of (x−0.3)6(x-0.3)^6 in p6(x)p_6(x) is

a6=−6.8,a_6=-6.8,

and the coefficient of (x−0.3)7(x-0.3)^7 in p7(x)p_7(x) is

a7=5.a_7=5.

They both agree that the graph of f(6)f^{(6)} looks like a straight line and decide to assume this is true.

They consider x1=0.5x_1=0.5 and want to use Lagrange's form of the remainder to find a bound on

∣f(0.5)−p5(0.5)∣.\left|f(0.5)-p_5(0.5)\right|.
(i)

Is knowing the value of a7a_7 necessary to calculate the error bound found using Lagrange's form of the remainder? Select all true statements:

  • The value of a7a_7 is necessary for these particular values of a6a_6 and x1x_1.
  • The value of a7a_7 is not necessary for these particular values of a6a_6 and x1x_1.
  • The value of a7a_7 would be necessary, regardless of the values of a6a_6 and x1x_1.
  • The value of a7a_7 would be necessary for some values of a6a_6 and x1x_1 and unnecessary for others.
(ii)

Find the smallest error bound guaranteed by Lagrange's form of the remainder:

∣f(0.5)−p5(0.5)∣≤ ?\left|f(0.5)-p_5(0.5)\right|\le \ ?

(c)

The fact that the graph in part (b) looks like a straight line with non-zero slope suggests that ff is a polynomial of degree 77. Discuss this conclusion, making clear what follows from an exact global assumption and what a graph alone can establish.

Solution

For a Taylor polynomial about x0=0.3x_0=0.3,

pn(x)=∑k=0nf(k)(0.3)k!(x−0.3)k.p_n(x)=\sum_{k=0}^{n}\frac{f^{(k)}(0.3)}{k!}(x-0.3)^k.

The coefficient of (x−0.3)k(x-0.3)^k is therefore f(k)(0.3)/k!f^{(k)}(0.3)/k!. Since k!>0k!>0, the sign of that coefficient is the sign of the corresponding derivative.

(a)

Consecutive Taylor polynomials differ by a single term:

pk(x)−pk−1(x)=f(k)(x0)k!(x−x0)k.p_k(x)-p_{k-1}(x) =\frac{f^{(k)}(x_0)}{k!}(x-x_0)^k.

The polynomial p1p_1 is decreasing at x0x_0, so

f′(0.3)<0.f'(0.3)<0.

Because p2=p1p_2=p_1, its quadratic coefficient vanishes, so

f′′(0.3)=0.f''(0.3)=0.

For x>x0x>x_0, the factor (x−x0)k(x-x_0)^k is positive. The recorded signs of p3−p2p_3-p_2, p4−p3p_4-p_3 and p5−p4p_5-p_4 therefore give

f(3)(0.3)>0,f(4)(0.3)>0,f(5)(0.3)<0.f^{(3)}(0.3)>0,\qquad f^{(4)}(0.3)>0,\qquad f^{(5)}(0.3)<0.

Thus the selections are:

  • zero: f′′(0.3){f''(0.3)};
  • positive: f(3)(0.3),f(4)(0.3){f^{(3)}(0.3),f^{(4)}(0.3)};
  • negative: f′(0.3),f(5)(0.3){f'(0.3),f^{(5)}(0.3)}.
(b)(i)

The Lagrange remainder for p5p_5 involves f(6)(c)f^{(6)}(c) for some cc between 0.30.3 and 0.50.5. The value a6a_6 gives f(6)(0.3)f^{(6)}(0.3), but the assumed straight-line graph of f(6)f^{(6)} also needs its slope to determine the largest absolute value on the interval. That slope is determined by a7a_7.

For these particular values, the first statement is true:

a7 is necessary for these particular values of a6 and x1.{\text{$a_7$ is necessary for these particular values of $a_6$ and $x_1$.}}

The fourth statement is also true in general: if x1=x0x_1=x_0, the error is zero without knowing a7a_7, whereas over a nontrivial interval the slope can change the maximum of ∣f(6)∣|f^{(6)}|. The second and third statements are false.

(b)(ii)

The Taylor coefficients give

f(6)(0.3)=6!a6=720(−6.8)=−4896f^{(6)}(0.3)=6!a_6=720(-6.8)=-4896

and

f(7)(0.3)=7!a7=5040(5)=25200.f^{(7)}(0.3)=7!a_7=5040(5)=25200.

Because f(6)f^{(6)} is assumed to be a straight line,

f(6)(x)=−4896+25200(x−0.3).f^{(6)}(x) =-4896+25200(x-0.3).

On the interval [0.3,0.5][0.3,0.5],

f(6)(0.3)=−4896,f(6)(0.5)=−4896+25200(0.2)=144.f^{(6)}(0.3)=-4896,\qquad f^{(6)}(0.5)=-4896+25200(0.2)=144.

A linear function takes its extreme values on a closed interval at the endpoints. Therefore

max⁡0.3≤c≤0.5∣f(6)(c)∣=max⁡{∣−4896∣,∣144∣}=4896.\max_{0.3\le c\le0.5}|f^{(6)}(c)| =\max\{|-4896|,|144|\} =4896.

Lagrange's form of the remainder for the degree-five polynomial is

f(0.5)−p5(0.5)=f(6)(c)6!(0.5−0.3)6f(0.5)-p_5(0.5) =\frac{f^{(6)}(c)}{6!}(0.5-0.3)^6

for some c∈(0.3,0.5)c\in(0.3,0.5). Consequently,

∣f(0.5)−p5(0.5)∣≤48966!(0.2)6=6.8(0.2)6=0.0004352.\begin{aligned} \left|f(0.5)-p_5(0.5)\right| &\le \frac{4896}{6!}(0.2)^6\\ &=6.8(0.2)^6\\ &={0.0004352}. \end{aligned}
(c)

If f(6)f^{(6)} is assumed to be exactly a straight line with non-zero slope on all of R\mathbb R, then f(7)f^{(7)} is a non-zero constant and f(8)=0f^{(8)}=0. Integrating this identity repeatedly shows that ff is a polynomial of degree exactly seven:

f is a polynomial of degree 7.{f\text{ is a polynomial of degree }7}.

A graph that merely looks linear, or is known to be linear only on the interval used for the error bound, does not establish this global conclusion; it supports the assumption locally but cannot determine ff outside that interval.

The plots encode derivative signs through Taylor coefficients. The sixth and seventh coefficients turn the straight-line assumption for f(6)f^{(6)} into a bound on its maximum, which is the quantity Lagrange's remainder needs.

[THEOREM]

Convergence has a central interval

Every real power series has a radius R∈[0,∞]R\in[0,\infty] with the following behaviour:

  • absolute convergence for ∣x−a∣<R|x-a|<R;
  • divergence for ∣x−a∣>R|x-a|>R;
  • separate endpoint behaviour when 0<R<∞0<R<\infty.
[THEOREM]

Root test

If

lim⁡n→∞∣an∣n=L,\lim_{n\to\infty}\sqrt[n]{|a_n|}=L,

then:

  • L<1L<1 implies absolute convergence;
  • L>1L>1 implies divergence;
  • L=1L=1 gives no conclusion.
[THEOREM]

Alternating-series test

If bn≥0b_n\ge0, bn+1≤bnb_{n+1}\le b_n and bn→0b_n\to0, then

∑n=0∞(−1)nbn\sum_{n=0}^{\infty}(-1)^n b_n

converges.

[EXAMPLE]

A power series and its endpoints

It is “play with series” night and Chelsea and Finn ask you to consider the power series

∑n=1∞(1n+(−1)nn)(x−7)n6n.(1)\sum_{n=1}^{\infty} \left(\frac{1}{\sqrt n}+\frac{(-1)^n}{n}\right) \frac{(x-7)^n}{6^n}. \tag{1}

(a)

Let

an=1n+(−1)nn.a_n=\frac{1}{\sqrt n}+\frac{(-1)^n}{n}.

Which of the following statements is true?

  • an>0a_n>0 for all n≥1n\ge1;
  • ana_n takes both positive and negative values at an infinite number of positive integers nn;
  • an>0a_n>0 for all n>1n>1;
  • an>0a_n>0 if nn is odd and an<0a_n<0 if nn is even.

(b)

Chelsea asks you to use an appropriate criterion to find the open interval of convergence I=(a,b)I=(a,b) for the power series (1) and to enter the values of aa and bb.

(c)

Determine what happens at the endpoints x=ax=a and x=bx=b. Select the true statements:

  • The power series (1) at x=bx=b is convergent.
  • The power series (1) at x=ax=a is not convergent.
  • The power series (1) at x=bx=b is not convergent.
  • The power series (1) at x=ax=a is convergent.

In a few sentences, justify your answers, explaining your reasoning.

Solution

For n=1n=1,

a1=1−1=0.a_1=1-1=0.

If nn is even, then

an=1n+1n>0.a_n=\frac1{\sqrt n}+\frac1n>0.

If nn is odd and n>1n>1, then

an=1n−1n=n−1n>0.a_n=\frac1{\sqrt n}-\frac1n =\frac{\sqrt n-1}{n}>0.

Hence the correct statement in part (a) is

an>0 for all n>1.{a_n>0\text{ for all }n>1.}

For n>1n>1,

1n−1n≤an≤1n+1n.\frac1{\sqrt n}-\frac1n \le a_n \le\frac1{\sqrt n}+\frac1n.

Both bounds have nnth root tending to 11, so

lim⁡n→∞∣an∣n=1.\lim_{n\to\infty}\sqrt[n]{|a_n|}=1.

Apply the root test to the general term of (1):

∣an(x−7)n6n∣n=∣an∣n∣x−7∣6⟶∣x−7∣6.\sqrt[n]{ \left|a_n\frac{(x-7)^n}{6^n}\right|} =\sqrt[n]{|a_n|}\frac{|x-7|}{6} \longrightarrow\frac{|x-7|}{6}.

The series converges absolutely when

∣x−7∣6<1⟺∣x−7∣<6.\frac{|x-7|}{6}<1 \quad\Longleftrightarrow\quad |x-7|<6.

Thus the open interval is

I=(1,13),a=1,b=13.{I=(1,13),\qquad a=1,\quad b=13.}

The root test does not decide the endpoints, so they must be substituted into the original series.

At x=b=13x=b=13, the factor (x−7)/6(x-7)/6 is 11 and the series becomes

∑n=1∞an.\sum_{n=1}^{\infty}a_n.

For n≥4n\ge4,

an≥1n−1n≥12n.a_n\ge\frac1{\sqrt n}-\frac1n \ge\frac1{2\sqrt n}.

The comparison series ∑1/n\sum 1/\sqrt n diverges, so the series at x=bx=b is not convergent.

At x=a=1x=a=1, the factor (x−7)/6(x-7)/6 is −1-1 and the series becomes

∑n=1∞(−1)nan=∑n=1∞(−1)nn+∑n=1∞1n.\sum_{n=1}^{\infty}(-1)^na_n =\sum_{n=1}^{\infty}\frac{(-1)^n}{\sqrt n} +\sum_{n=1}^{\infty}\frac1n.

The first series converges by the alternating-series test, while the second is the divergent harmonic series. Therefore the series at x=ax=a is also not convergent.

Thus the endpoint statements are

the series at x=a is not convergent and the series at x=b is not convergent.{ \text{the series at }x=a\text{ is not convergent and the series at }x=b \text{ is not convergent}. }

The radius depends only on the nnth-root limit of the slowly varying coefficients, which is 11. The endpoints need separate arguments: at the left endpoint the alternating 1/n1/\sqrt n part converges but the harmonic part does not and at the right endpoint the positive 1/n1/\sqrt n behaviour forces divergence.

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