MATH 141 Calculus 2 • McGill University, Montreal

Corrected exercises: Taylor polynomials and error bounds (MATH 141)

This is the corrected exercise set for the last chapter of MATH 141, Calculus 2, at McGill University: Taylor polynomials and their error bounds, sections 11.10 and 11.11 of Stewart. Every approximation is done by hand, in fractions and small decimals, and every bound is a simple fraction proved without a machine: e0.2≈458375e^{0.2} \approx \frac{458}{375} within 112000\frac{1}{12000}, 1.13≈929900\sqrt[3]{1.1} \approx \frac{929}{900} within 116200\frac{1}{16200}, ln⁡2≈8421215\ln 2 \approx \frac{842}{1215} within 16804\frac{1}{6804}.

The thread running through the whole set: an approximation is a value AND a guaranteed bound. The bound comes from the remainder, controlled on the WHOLE interval between the centre and the point: in Taylor's inequality, MM bounds ∣f(n+1)∣\lvert f^{(n+1)}\rvert at its worst point of that interval, never at the centre; when the Taylor series alternates at the point, the first omitted term bounds the error and gives its sign; when neither is convenient, the tail is compared with a geometric series.

The traps named explicitly in the solutions: taking MM at the centre of the interval and producing a bound that the function violates, using the first omitted term on a series whose terms are all positive, forgetting that T3=T4T_3 = T_4 for the sine, plugging degrees into a formula written in radians, reading an error bound as a number of correct decimals, carrying an MM found on one interval to another, and centring at 00 by habit when a nearer centre is available.

10 corrected exercises • 100 points • 150 minutes

Revision sheet for this chapter → Every MATH 141 chapter →

Course recap

  • • Tn(x)=∑k=0nf(k)(a)k!(x−a)kT_n(x) = \sum_{k=0}^{n}\frac{f^{(k)}(a)}{k!}(x - a)^k and Rn(x)=f(x)−Tn(x)R_n(x) = f(x) - T_n(x).
  • • Taylor's inequality: if ∣f(n+1)(x)∣≤M\lvert f^{(n+1)}(x)\rvert \le M for ALL ∣x−a∣≤d\lvert x - a\rvert \le d, then ∣Rn(x)∣≤M(n+1)!∣x−a∣n+1\lvert R_n(x)\rvert \le \frac{M}{(n + 1)!}\lvert x - a\rvert^{n+1} there.
  • • Lagrange form: Rn(x)=f(n+1)(z)(n+1)!(x−a)n+1R_n(x) = \frac{f^{(n+1)}(z)}{(n + 1)!}(x - a)^{n+1} for some zz between aa and xx; a constant sign of f(n+1)f^{(n+1)} gives the sign of the error.
  • • Alternating estimate: if the series at xx alternates with terms decreasing to 00, the error is less than the first omitted term and has its sign.
  • • When Tn=Tn+1T_n = T_{n+1} (odd or even functions at 00), apply the inequality with n+1n + 1.
  • • Maclaurin table: ex=∑xkk!e^x = \sum\frac{x^k}{k!}, sin⁡x=∑(−1)kx2k+1(2k+1)!\sin x = \sum\frac{(-1)^k x^{2k+1}}{(2k + 1)!}, cos⁡x=∑(−1)kx2k(2k)!\cos x = \sum\frac{(-1)^k x^{2k}}{(2k)!}, ln⁡(1+x)=∑k≥1(−1)k+1xkk\ln(1 + x) = \sum_{k \ge 1}\frac{(-1)^{k+1}x^k}{k} for −1<x≤1-1 < x \le 1.

Part A: the basics (/50)

Exercise 1: Building T_n, and what its graph says about it

The Taylor polynomial of degree nn of ff at aa is Tn(x)=∑k=0nf(k)(a)k!(x−a)kT_n(x) = \sum_{k=0}^{n}\frac{f^{(k)}(a)}{k!}(x - a)^k. It is the only polynomial of degree at most nn whose value and first nn derivatives at aa agree with those of ff. It is built from information at ONE point, so it can only be trusted near that point; how near is the whole subject of this chapter.

The figure shows y=sin⁡xy = \sin x and three of its Taylor polynomials at 00 on [−4,4][-4, 4].

-4-3-2-11234-3-2-1123T₁T₃T₅sin x
  • a) Compute T1T_1, T3T_3 and T5T_5 of sin⁡x\sin x at a=0a = 0. Explain why T4=T3T_4 = T_3 and T6=T5T_6 = T_5.
  • b) Using the figure, say roughly up to which ∣x∣\lvert x\rvert each polynomial stays close to sin⁡x\sin x, and on which side of sin⁡x\sin x each one lies for small x>0x > 0.
  • c) Compute T3T_3 of f(x)=ln⁡xf(x) = \ln x at a=1a = 1.
  • d) Compute T2T_2 of f(x)=xf(x) = \sqrt{x} at a=4a = 4, and check the three conditions that define it.
  • e) Explain why no polynomial TnT_n of the figure is good on the whole window, and what raising the degree changes.
Show the solution

Answers

  • a) T1=xT_1 = x, T3=x−x36T_3 = x - \frac{x^3}{6}, T5=x−x36+x5120T_5 = x - \frac{x^3}{6} + \frac{x^5}{120}; the even derivatives of sin⁡\sin vanish at 00.
  • b) Roughly ∣x∣<1\lvert x\rvert < 1, 22, 33; for small x>0x > 0: T1T_1 above, T3T_3 below, T5T_5 above.
  • c) T3(x)=(x−1)−(x−1)22+(x−1)33T_3(x) = (x - 1) - \frac{(x - 1)^2}{2} + \frac{(x - 1)^3}{3}
  • d) T2(x)=2+x−44−(x−4)264T_2(x) = 2 + \frac{x - 4}{4} - \frac{(x - 4)^2}{64}
  • e) TnT_n copies ff at one point only; a higher degree widens the zone of good fit but never makes it the whole line.

a) The derivatives of sin⁡x\sin x cycle: sin⁡x\sin x, cos⁡x\cos x, −sin⁡x-\sin x, −cos⁡x-\cos x, sin⁡x\sin x, …\dots, so at 00 they take the values 0,1,0,−1,0,1,0,…0, 1, 0, -1, 0, 1, 0, \dots Hence T1(x)=0+1⋅x=xT_1(x) = 0 + 1 \cdot x = x, T3(x)=x+02!x2+−13!x3=x−x36T_3(x) = x + \frac{0}{2!}x^2 + \frac{-1}{3!}x^3 = x - \frac{x^3}{6}, and T5(x)=x−x36+15!x5=x−x36+x5120T_5(x) = x - \frac{x^3}{6} + \frac{1}{5!}x^5 = x - \frac{x^3}{6} + \frac{x^5}{120}. Since f(4)(0)=sin⁡0=0f^{(4)}(0) = \sin 0 = 0, the term of degree 44 is 00 and T4=T3T_4 = T_3; likewise f(6)(0)=−sin⁡0=0f^{(6)}(0) = -\sin 0 = 0 gives T6=T5T_6 = T_5. This is not a detail: T3T_3 is ALSO T4T_4, and Exercises 2, 4 and 6 show that using it as T4T_4 gives an error bound twenty to fifty times better.

b) Reading the figure: the orange line T1=xT_1 = x leaves the sine curve visibly around ∣x∣≈1\lvert x\rvert \approx 1; the green cubic T3T_3 holds until about ∣x∣≈2\lvert x\rvert \approx 2; the red T5T_5 until about ∣x∣≈3\lvert x\rvert \approx 3. For small x>0x > 0, T1T_1 is ABOVE sin⁡x\sin x, T3T_3 BELOW, T5T_5 ABOVE again: each new term overcorrects the previous one, because the terms of the sine series alternate in sign. At x=1x = 1: T1(1)=1T_1(1) = 1, T3(1)=56≈0.833T_3(1) = \frac{5}{6} \approx 0.833, T5(1)=101120≈0.842T_5(1) = \frac{101}{120} \approx 0.842, and sin⁡1\sin 1 lies between the last two. Exercise 4 turns this alternation into a bound.

c) f(x)=ln⁡xf(x) = \ln x, f′(x)=1xf'(x) = \frac{1}{x}, f′′(x)=−1x2f''(x) = -\frac{1}{x^2}, f′′′(x)=2x3f'''(x) = \frac{2}{x^3}; at 11: 00, 11, −1-1, 22. So T3(x)=0+(x−1)−12!(x−1)2+23!(x−1)3=(x−1)−(x−1)22+(x−1)33T_3(x) = 0 + (x - 1) - \frac{1}{2!}(x - 1)^2 + \frac{2}{3!}(x - 1)^3 = (x - 1) - \frac{(x - 1)^2}{2} + \frac{(x - 1)^3}{3}. Two slips cost marks here: expanding in powers of xx instead of x−1x - 1 (the polynomial is centred at 11, keep the powers of x−1x - 1), and forgetting the k!k!, which turns the last coefficient into 22. With u=x−1u = x - 1 one recognizes the first terms of ln⁡(1+u)=u−u22+u33−⋯\ln(1 + u) = u - \frac{u^2}{2} + \frac{u^3}{3} - \cdots, a free check.

d) f(x)=x1/2f(x) = x^{1/2}, f′(x)=12x−1/2f'(x) = \frac{1}{2}x^{-1/2}, f′′(x)=−14x−3/2f''(x) = -\frac{1}{4}x^{-3/2}. At 44: f(4)=2f(4) = 2, f′(4)=12⋅12=14f'(4) = \frac{1}{2} \cdot \frac{1}{2} = \frac{1}{4}, f′′(4)=−14⋅18=−132f''(4) = -\frac{1}{4} \cdot \frac{1}{8} = -\frac{1}{32}. So T2(x)=2+14(x−4)−132⋅2(x−4)2=2+x−44−(x−4)264T_2(x) = 2 + \frac{1}{4}(x - 4) - \frac{1}{32 \cdot 2}(x - 4)^2 = 2 + \frac{x - 4}{4} - \frac{(x - 4)^2}{64}. Check: T2(4)=2=f(4)T_2(4) = 2 = f(4); T2′(x)=14−x−432T_2'(x) = \frac{1}{4} - \frac{x - 4}{32} gives T2′(4)=14=f′(4)T_2'(4) = \frac{1}{4} = f'(4); T2′′(x)=−132=f′′(4)T_2''(x) = -\frac{1}{32} = f''(4). The classic error is the coefficient −132-\frac{1}{32} instead of −164-\frac{1}{64}: then T2′′=−116T_2'' = -\frac{1}{16} and the third condition fails, which is exactly how to catch it.

e) A Taylor polynomial knows ff only through f(a),f′(a),…,f(n)(a)f(a), f'(a), \dots, f^{(n)}(a): it copies the shape of ff at 00 and extrapolates. Far from 00 the polynomial is dominated by its highest power and runs off to ±∞\pm\infty, while sin⁡x\sin x stays between −1-1 and 11, so no TnT_n can follow the sine on the whole real line. Raising the degree widens the zone where the fit is good (about 11, 22, 33 for n=1,3,5n = 1, 3, 5), and near 00 the gap shrinks like the first neglected power: x3x^3, then x5x^5, then x7x^7. Quantifying that gap, with a bound that is GUARANTEED rather than read on a picture, is the job of Taylor's inequality.

Exercise 2: Taylor's inequality: M bounds the derivative on the whole interval

Taylor's inequality. If ∣f(n+1)(x)∣≤M\lvert f^{(n+1)}(x)\rvert \le M for ALL xx with ∣x−a∣≤d\lvert x - a\rvert \le d, then the remainder Rn(x)=f(x)−Tn(x)R_n(x) = f(x) - T_n(x) satisfies ∣Rn(x)∣≤M(n+1)!∣x−a∣n+1\lvert R_n(x)\rvert \le \frac{M}{(n + 1)!}\lvert x - a\rvert^{n+1} for ∣x−a∣≤d\lvert x - a\rvert \le d.

Everything rests on the word ALL: MM is a bound on the whole interval, not the value of f(n+1)f^{(n+1)} at the centre. The figure shows y=2(1+x)3y = \frac{2}{(1 + x)^3}, the third derivative of ln⁡(1+x)\ln(1 + x), on [−0.5,0.5][-0.5, 0.5].

-0.5-0.250.250.5246810121416value at the centre: 2left end: 16y = 2/(1 + x)³
  • a) Bound the error of ex≈1+x+x22e^x \approx 1 + x + \frac{x^2}{2} for ∣x∣≤0.5\lvert x\rvert \le 0.5.
  • b) Bound the error of ln⁡(1+x)≈x−x22\ln(1 + x) \approx x - \frac{x^2}{2} for ∣x∣≤0.5\lvert x\rvert \le 0.5. Show that the value M=f′′′(0)M = f'''(0) would give a bound that is FALSE.
  • c) Same approximation, but only for 0≤x≤0.50 \le x \le 0.5. What changes, and why?
  • d) Bound the error of cos⁡x≈1−x22\cos x \approx 1 - \frac{x^2}{2} for ∣x∣≤0.2\lvert x\rvert \le 0.2, first with n=2n = 2, then with n=3n = 3. Which is right, and which is better?
  • e) State a rule for locating the worst point of ∣f(n+1)∣\lvert f^{(n+1)}\rvert on the interval, with the three families of a) to d).
Show the solution

Answers

  • a) M=e0.5<2M = e^{0.5} < 2, so ∣R2∣≤2(0.5)36=124\lvert R_2\rvert \le \frac{2(0.5)^3}{6} = \frac{1}{24}
  • b) M=16M = 16 (at x=−0.5x = -0.5), ∣R2∣≤13\lvert R_2\rvert \le \frac{1}{3}; with M=2M = 2 one would claim 124\frac{1}{24}, but the error at −0.5-0.5 is ln⁡2−58≈0.068\ln 2 - \frac{5}{8} \approx 0.068.
  • c) On [0,0.5][0, 0.5] the worst point is x=0x = 0: M=2M = 2 and ∣R2∣≤124\lvert R_2\rvert \le \frac{1}{24} is now valid.
  • d) n=2n = 2: ≤13750\le \frac{1}{3750} (with M=0.2M = 0.2); n=3n = 3, since T2=T3T_2 = T_3: ≤115000\le \frac{1}{15000}, both right, the second four times better.
  • e) If ∣f(n+1)∣\lvert f^{(n+1)}\rvert is monotone, its max is at an END of the interval; check both ends. sin⁡\sin and cos⁡\cos: M=1M = 1 always works.

a) Here n=2n = 2, a=0a = 0, d=0.5d = 0.5 and f′′′(x)=exf'''(x) = e^x. On [−0.5,0.5][-0.5, 0.5] the exponential is increasing, so its largest value is at the RIGHT end: M=e0.5=eM = e^{0.5} = \sqrt{e}. No calculator needed to bound it: e<4e < 4, so e<2\sqrt{e} < 2. Then ∣R2(x)∣≤23!(0.5)3=26⋅18=124≈0.042\lvert R_2(x)\rvert \le \frac{2}{3!}(0.5)^3 = \frac{2}{6} \cdot \frac{1}{8} = \frac{1}{24} \approx 0.042 for all ∣x∣≤0.5\lvert x\rvert \le 0.5. A sharper MM is allowed, 1.652=2.7225>e1.65^2 = 2.7225 > e gives e<1.65\sqrt{e} < 1.65 and the bound 1.6548≈0.034\frac{1.65}{48} \approx 0.034, but any number ABOVE the true maximum is a valid MM. The one thing that is not allowed is a number below it.

b) f(x)=ln⁡(1+x)f(x) = \ln(1 + x), f′(x)=11+xf'(x) = \frac{1}{1 + x}, f′′(x)=−1(1+x)2f''(x) = -\frac{1}{(1 + x)^2}, f′′′(x)=2(1+x)3f'''(x) = \frac{2}{(1 + x)^3}. On [−0.5,0.5][-0.5, 0.5], 1+x1 + x ranges over [0.5,1.5][0.5, 1.5] and 2(1+x)3\frac{2}{(1 + x)^3} is DECREASING, so its maximum is at the LEFT end: M=2(0.5)3=16M = \frac{2}{(0.5)^3} = 16, the red point of the figure. Taylor's inequality gives ∣R2(x)∣≤166(0.5)3=13\lvert R_2(x)\rvert \le \frac{16}{6}(0.5)^3 = \frac{1}{3}. Weak, but guaranteed. Now the tempting shortcut M=f′′′(0)=2M = f'''(0) = 2 would claim ∣R2∣≤26⋅18=124≈0.042\lvert R_2\rvert \le \frac{2}{6} \cdot \frac{1}{8} = \frac{1}{24} \approx 0.042. Test it at x=−0.5x = -0.5: f(−0.5)=ln⁡12=−ln⁡2≈−0.693f(-0.5) = \ln\frac{1}{2} = -\ln 2 \approx -0.693 and T2(−0.5)=−0.5−0.125=−0.625T_2(-0.5) = -0.5 - 0.125 = -0.625, so the true error is ln⁡2−58≈0.068\ln 2 - \frac{5}{8} \approx 0.068, larger than 0.0420.042. A bound that the function itself violates is not a bound; on a final it is worth zero, whatever the arithmetic.

c) On [0,0.5][0, 0.5] the same decreasing function 2(1+x)3\frac{2}{(1 + x)^3} has its maximum at x=0x = 0, the left end of THIS interval, so M=2M = 2 is now correct and ∣R2(x)∣≤26(0.5)3=124\lvert R_2(x)\rvert \le \frac{2}{6}(0.5)^3 = \frac{1}{24} for 0≤x≤0.50 \le x \le 0.5. At x=0.5x = 0.5 the true error is ln⁡1.5−0.375≈0.031\ln 1.5 - 0.375 \approx 0.031, below 124\frac{1}{24} as it must be. The function, the polynomial and the formula are those of b); only the interval changed, and with it the worst point. This is why every MM on a copy is written with its interval: ∣f′′′(x)∣≤2\lvert f'''(x)\rvert \le 2 for 0≤x≤0.50 \le x \le 0.5.

d) With n=2n = 2: f′′′(x)=sin⁡xf'''(x) = \sin x, and on [−0.2,0.2][-0.2, 0.2], ∣sin⁡x∣≤∣x∣≤0.2\lvert\sin x\rvert \le \lvert x\rvert \le 0.2, so M=0.2M = 0.2 and ∣R2∣≤0.26(0.2)3=0.00166=13750≈0.00027\lvert R_2\rvert \le \frac{0.2}{6}(0.2)^3 = \frac{0.0016}{6} = \frac{1}{3750} \approx 0.00027. (With the lazy M=1M = 1: 0.0086≈0.0013\frac{0.008}{6} \approx 0.0013, also correct.) With n=3n = 3: since cos⁡\cos has no x3x^3 term, T3=T2T_3 = T_2, and the remainder is ALSO R3R_3, controlled by f(4)(x)=cos⁡xf^{(4)}(x) = \cos x, ∣cos⁡x∣≤1\lvert\cos x\rvert \le 1: ∣R3∣≤124(0.2)4=0.001624=115000≈0.000067\lvert R_3\rvert \le \frac{1}{24}(0.2)^4 = \frac{0.0016}{24} = \frac{1}{15000} \approx 0.000067. Both bounds are true; the second is four times better than the first and twenty times better than the lazy one. The true error at 0.20.2 is about 0.00006660.0000666: the n=3n = 3 bound is practically exact.

e) The worst point of ∣f(n+1)∣\lvert f^{(n+1)}\rvert is found like any maximum on a closed interval, and in practice ∣f(n+1)∣\lvert f^{(n+1)}\rvert is monotone on it, so the maximum sits at an END. Exponentials exe^{x}: increasing, the RIGHT end (a). Powers of 11+x\frac{1}{1 + x}, which is where ln⁡(1+x)\ln(1 + x) and (1+x)k(1 + x)^k lead: decreasing, the LEFT end (b, c). Sine and cosine: M=1M = 1 always works, and a smaller MM is available near 00 (d). Two rules follow. Never take MM at the centre unless the centre IS the worst point, as in c). And when Tn=Tn+1T_n = T_{n+1}, use n+1n + 1 in the inequality: the bound gains a full power of ∣x−a∣\lvert x - a\rvert.

Exercise 3: By hand, with a guaranteed bound: e to the 0.2 and the cube root of 1.1

On a MATH 141 exam, approximate means: give a value computed by hand AND a bound on its error that you can prove, with the sign of the error when it is available. A value alone, however accurate, answers half the question.

The figure shows y=1+x3y = \sqrt[3]{1 + x} with its Taylor polynomials T1T_1 and T2T_2 at 00 on [−1,3][-1, 3].

-1-0.50.511.522.530.511.522.5T₁∛(1+x)T₂
  • a) Use T3T_3 of exe^x at 00 to approximate e0.2e^{0.2}, as an exact fraction.
  • b) Bound the error with Taylor's inequality. Justify your MM without a calculator.
  • c) Is T3(0.2)T_3(0.2) an overestimate or an underestimate? Deduce an interval that contains e0.2e^{0.2}.
  • d) Use T2T_2 of (1+x)1/3(1 + x)^{1/3} at 00 to approximate 1.13\sqrt[3]{1.1}, as a fraction.
  • e) Bound the error, decide its sign with the help of the figure, and say what goes wrong if MM is evaluated at x=0.1x = 0.1.
Show the solution

Answers

  • a) e0.2≈1+15+150+1750=458375≈1.221333e^{0.2} \approx 1 + \frac{1}{5} + \frac{1}{50} + \frac{1}{750} = \frac{458}{375} \approx 1.221333
  • b) M=e0.2<1.25M = e^{0.2} < 1.25 (as 1.255>3>e1.25^5 > 3 > e): ∣R3∣≤1.25(0.2)424=112000\lvert R_3\rvert \le \frac{1.25(0.2)^4}{24} = \frac{1}{12000}
  • c) Underestimate: 458375<e0.2<458375+112000\frac{458}{375} < e^{0.2} < \frac{458}{375} + \frac{1}{12000}, so 1.22133<e0.2<1.221421.22133 < e^{0.2} < 1.22142
  • d) 1.13≈1+130−1900=929900≈1.032222\sqrt[3]{1.1} \approx 1 + \frac{1}{30} - \frac{1}{900} = \frac{929}{900} \approx 1.032222
  • e) ∣R2∣≤1027⋅(0.1)36=116200\lvert R_2\rvert \le \frac{10}{27} \cdot \frac{(0.1)^3}{6} = \frac{1}{16200}, underestimate; MM taken at 0.10.1 gives a smaller number that the true error exceeds.

a) exe^x is its own derivative, so every coefficient is 1k!\frac{1}{k!} and T3(x)=1+x+x22+x36T_3(x) = 1 + x + \frac{x^2}{2} + \frac{x^3}{6}. At x=0.2=15x = 0.2 = \frac{1}{5}: T3(0.2)=1+15+150+1750T_3(0.2) = 1 + \frac{1}{5} + \frac{1}{50} + \frac{1}{750}. Over the common denominator 750750: 750+150+15+1750=916750=458375\frac{750 + 150 + 15 + 1}{750} = \frac{916}{750} = \frac{458}{375}, that is 1.221333…1.221333\ldots Working in fractions keeps the arithmetic exact; the decimal is written only at the end.

b) n=3n = 3, so we need M≥∣f(4)(x)∣=exM \ge \lvert f^{(4)}(x)\rvert = e^x for 0≤x≤0.20 \le x \le 0.2. The exponential is increasing: the worst point is x=0.2x = 0.2, and M=e0.2M = e^{0.2}, the very number we are approximating. It is bounded by something simpler. Crude and valid: e0.2<e<3e^{0.2} < e < 3, which gives ∣R3∣≤3(0.2)424=3⋅0.001624=0.0002\lvert R_3\rvert \le \frac{3(0.2)^4}{24} = \frac{3 \cdot 0.0016}{24} = 0.0002. Better: 1.252=1.56251.25^2 = 1.5625, 1.254≈2.441.25^4 \approx 2.44, 1.255≈3.05>e1.25^5 \approx 3.05 > e, so e0.2<1.25e^{0.2} < 1.25 and ∣R3∣≤1.25⋅0.001624=0.00224=112000≈0.000083\lvert R_3\rvert \le \frac{1.25 \cdot 0.0016}{24} = \frac{0.002}{24} = \frac{1}{12000} \approx 0.000083. What is NOT acceptable is M=e0=1M = e^0 = 1, the value at the centre, which sits at the wrong end of the interval.

c) The remainder has a definite sign here. All the terms of the series of e0.2e^{0.2} are positive, so the part left out, (0.2)424+(0.2)5120+⋯\frac{(0.2)^4}{24} + \frac{(0.2)^5}{120} + \cdots, is positive: T3(0.2)T_3(0.2) is an UNDERESTIMATE. (Equivalently, the Lagrange form of the remainder is ez24(0.2)4>0\frac{e^z}{24}(0.2)^4 > 0 for some zz between 00 and 0.20.2.) So 458375<e0.2<458375+112000\frac{458}{375} < e^{0.2} < \frac{458}{375} + \frac{1}{12000}, i.e. 1.22133<e0.2<1.221421.22133 < e^{0.2} < 1.22142. The interval is the answer a marker wants: it is guaranteed, and its width says how good the approximation is.

d) f(x)=(1+x)1/3f(x) = (1 + x)^{1/3}, f′(x)=13(1+x)−2/3f'(x) = \frac{1}{3}(1 + x)^{-2/3}, f′′(x)=−29(1+x)−5/3f''(x) = -\frac{2}{9}(1 + x)^{-5/3}; at 00: 11, 13\frac{1}{3}, −29-\frac{2}{9}. So T2(x)=1+x3−29⋅x22=1+x3−x29T_2(x) = 1 + \frac{x}{3} - \frac{2}{9} \cdot \frac{x^2}{2} = 1 + \frac{x}{3} - \frac{x^2}{9}, the first terms of the binomial series with k=13k = \frac{1}{3}. At x=0.1x = 0.1: 1+130−1900=900+30−1900=929900≈1.0322221 + \frac{1}{30} - \frac{1}{900} = \frac{900 + 30 - 1}{900} = \frac{929}{900} \approx 1.032222.

e) f′′′(x)=1027(1+x)−8/3f'''(x) = \frac{10}{27}(1 + x)^{-8/3}, positive and DECREASING on [0,0.1][0, 0.1]: the worst point is the left end, M=f′′′(0)=1027M = f'''(0) = \frac{10}{27} (here the centre IS the worst point, and that has to be said, not assumed). Then ∣R2(0.1)∣≤1027⋅(0.1)33!=1027⋅6000=116200≈0.000062\lvert R_2(0.1)\rvert \le \frac{10}{27} \cdot \frac{(0.1)^3}{3!} = \frac{10}{27 \cdot 6000} = \frac{1}{16200} \approx 0.000062. Sign: R2(0.1)=f′′′(z)6(0.1)3R_2(0.1) = \frac{f'''(z)}{6}(0.1)^3 with f′′′>0f''' > 0, so the error is positive and T2T_2 is an UNDERESTIMATE: 929900<1.13<929900+116200\frac{929}{900} < \sqrt[3]{1.1} < \frac{929}{900} + \frac{1}{16200}. The figure agrees: for x>0x > 0 the green parabola T2T_2 runs below the curve, while the tangent line T1T_1 runs above it. If MM is evaluated at x=0.1x = 0.1 instead, one gets 116200(1.1)−8/3\frac{1}{16200}(1.1)^{-8/3}, about 0.0000480.000048; the true error is about 0.0000580.000058 (a machine confirms it afterwards), so that number is NOT a bound. The correct bound is barely above the true error, which is why the worst point matters.

Exercise 4: When the Taylor series alternates, the first omitted term does the job

The alternating series estimate: if bk>0b_k > 0 decreases to 00, the sum SS of ∑(−1)kbk\sum (-1)^k b_k satisfies ∣S−SN∣≤bN+1\lvert S - S_N\rvert \le b_{N+1}, the first omitted term, and S−SNS - S_N has the SIGN of that term. Evaluated at a number, many Taylor series alternate, and then this estimate gives a bound with no MM to find.

The figure shows the partial sums S1,S2,…,S6S_1, S_2, \dots, S_6 of arctan⁡12=12−(1/2)33+(1/2)55−⋯\arctan\frac{1}{2} = \frac{1}{2} - \frac{(1/2)^3}{3} + \frac{(1/2)^5}{5} - \cdots, with the value arctan⁡12\arctan\frac{1}{2} dashed.

12345670.450.460.470.480.490.50.51S₁ = 1/2S₂ = 11/24arctan(1/2)number of terms
  • a) Approximate sin⁡0.1\sin 0.1 by T3(0.1)T_3(0.1) and bound the error with the alternating series estimate, checking its hypotheses. Is T3(0.1)T_3(0.1) too large or too small?
  • b) Compare with Taylor's inequality used with n=3n = 3, then with n=4n = 4.
  • c) Approximate cos⁡0.5\cos 0.5 by T2(0.5)T_2(0.5), with a bound and the sign of the error.
  • d) Approximate arctan⁡12\arctan\frac{1}{2} by the first two terms of its series, with a bound and the sign. Why is Taylor's inequality of no practical use here?
  • e) For which of e−0.2e^{-0.2}, e0.2e^{0.2}, ln⁡1.2\ln 1.2 and ln⁡0.8\ln 0.8 does the alternating estimate apply to the Maclaurin series? Justify.
Show the solution

Answers

  • a) sin⁡0.1≈5996000\sin 0.1 \approx \frac{599}{6000}, error <(0.1)5120=112 000 000< \frac{(0.1)^5}{120} = \frac{1}{12\,000\,000}, T3(0.1)T_3(0.1) too small.
  • b) n=3n = 3: (0.1)424=1240 000\frac{(0.1)^4}{24} = \frac{1}{240\,000}, fifty times weaker; n=4n = 4 (as T4=T3T_4 = T_3): the same 112 000 000\frac{1}{12\,000\,000}.
  • c) cos⁡0.5≈78\cos 0.5 \approx \frac{7}{8}, 78<cos⁡0.5<78+1384\frac{7}{8} < \cos 0.5 < \frac{7}{8} + \frac{1}{384}
  • d) 1124<arctan⁡12<1124+1160\frac{11}{24} < \arctan\frac{1}{2} < \frac{11}{24} + \frac{1}{160}; bounding a high derivative of arctan⁡\arctan by hand is impractical.
  • e) Yes for e−0.2e^{-0.2} and ln⁡1.2\ln 1.2; no for e0.2e^{0.2} and ln⁡0.8\ln 0.8, whose terms all have the same sign.

a) sin⁡0.1=0.1−(0.1)33!+(0.1)55!−⋯\sin 0.1 = 0.1 - \frac{(0.1)^3}{3!} + \frac{(0.1)^5}{5!} - \cdots, and T3(0.1)=0.1−0.0016=600−16000=5996000≈0.0998333T_3(0.1) = 0.1 - \frac{0.001}{6} = \frac{600 - 1}{6000} = \frac{599}{6000} \approx 0.0998333. Hypotheses, one by one: the series alternates; its terms bk=(0.1)2k+1(2k+1)!b_k = \frac{(0.1)^{2k+1}}{(2k + 1)!} are positive and decreasing, since bk+1bk=(0.1)2(2k+2)(2k+3)<1\frac{b_{k+1}}{b_k} = \frac{(0.1)^2}{(2k + 2)(2k + 3)} < 1; and bk→0b_k \to 0. So ∣sin⁡0.1−T3(0.1)∣≤b2=(0.1)5120=10−5120=112 000 000≈8.3×10−8\lvert \sin 0.1 - T_3(0.1)\rvert \le b_2 = \frac{(0.1)^5}{120} = \frac{10^{-5}}{120} = \frac{1}{12\,000\,000} \approx 8.3 \times 10^{-8}. The first omitted term is POSITIVE, so the error sin⁡0.1−T3(0.1)\sin 0.1 - T_3(0.1) is positive: T3(0.1)T_3(0.1) is too SMALL, and 5996000<sin⁡0.1<5996000+112 000 000\frac{599}{6000} < \sin 0.1 < \frac{599}{6000} + \frac{1}{12\,000\,000}. Seven correct decimals from two terms.

b) Taylor's inequality with n=3n = 3: ∣f(4)(x)∣=∣sin⁡x∣≤1\lvert f^{(4)}(x)\rvert = \lvert\sin x\rvert \le 1, so ∣R3(0.1)∣≤(0.1)424=1240 000≈4.2×10−6\lvert R_3(0.1)\rvert \le \frac{(0.1)^4}{24} = \frac{1}{240\,000} \approx 4.2 \times 10^{-6}, true but fifty times weaker. With n=4n = 4, legitimate because T4=T3T_4 = T_3 for the sine (Exercise 1): ∣f(5)∣=∣cos⁡x∣≤1\lvert f^{(5)}\rvert = \lvert\cos x\rvert \le 1 and ∣R4(0.1)∣≤(0.1)5120\lvert R_4(0.1)\rvert \le \frac{(0.1)^5}{120}, exactly the alternating bound. The alternating estimate does automatically what Taylor's inequality does only if you remember that the even terms are zero, and it adds the SIGN, which Taylor's inequality never gives.

c) cos⁡0.5=1−(0.5)22+(0.5)424−⋯\cos 0.5 = 1 - \frac{(0.5)^2}{2} + \frac{(0.5)^4}{24} - \cdots alternates, with terms (0.5)2k(2k)!\frac{(0.5)^{2k}}{(2k)!} decreasing (ratio 0.25(2k+1)(2k+2)<1\frac{0.25}{(2k + 1)(2k + 2)} < 1) to 00. T2(0.5)=1−18=78T_2(0.5) = 1 - \frac{1}{8} = \frac{7}{8}. First omitted term: (0.5)424=116⋅24=1384≈0.0026\frac{(0.5)^4}{24} = \frac{1}{16 \cdot 24} = \frac{1}{384} \approx 0.0026, positive. Hence 78<cos⁡0.5<78+1384\frac{7}{8} < \cos 0.5 < \frac{7}{8} + \frac{1}{384}, that is 0.875<cos⁡0.5<0.87770.875 < \cos 0.5 < 0.8777. The true value is about 0.877580.87758: the error, 0.002580.00258, is almost exactly the first omitted term, because the terms after it are tiny. That is why this estimate is often SHARPER in practice: it uses the next term itself, while Taylor's inequality uses the worst value of a derivative over a whole interval.

d) arctan⁡x=x−x33+x55−⋯\arctan x = x - \frac{x^3}{3} + \frac{x^5}{5} - \cdots for ∣x∣≤1\lvert x\rvert \le 1. At x=12x = \frac{1}{2} the terms bk=(1/2)2k+12k+1b_k = \frac{(1/2)^{2k+1}}{2k + 1} are positive, decreasing (numerator divided by 44, denominator larger) and tend to 00. Two terms: 12−124=1124≈0.4583\frac{1}{2} - \frac{1}{24} = \frac{11}{24} \approx 0.4583. First omitted term: (1/2)55=1160=0.00625\frac{(1/2)^5}{5} = \frac{1}{160} = 0.00625, positive: 1124<arctan⁡12<1124+1160\frac{11}{24} < \arctan\frac{1}{2} < \frac{11}{24} + \frac{1}{160}. The figure shows the mechanism: S1=12S_1 = \frac{1}{2} above the dashed value, S2=1124S_2 = \frac{11}{24} below, and each partial sum lands on the other side, closer, so the value is always trapped between two consecutive sums. Taylor's inequality would need a bound on the fifth derivative of arctan⁡x\arctan x on [0,12][0, \frac{1}{2}], a rational function whose numerator is a polynomial of degree four: no one computes it on an exam, and the alternating estimate makes it unnecessary.

e) e−0.2=1−0.2+(0.2)22−(0.2)36+⋯e^{-0.2} = 1 - 0.2 + \frac{(0.2)^2}{2} - \frac{(0.2)^3}{6} + \cdots alternates, terms (0.2)kk!\frac{(0.2)^k}{k!} decreasing to 00: YES. e0.2e^{0.2}: every term is positive, the series does not alternate: NO, which is why Exercise 3 needed Taylor's inequality. ln⁡1.2=ln⁡(1+0.2)=0.2−(0.2)22+(0.2)33−⋯\ln 1.2 = \ln(1 + 0.2) = 0.2 - \frac{(0.2)^2}{2} + \frac{(0.2)^3}{3} - \cdots alternates, terms (0.2)kk\frac{(0.2)^k}{k} decreasing to 00: YES. ln⁡0.8=ln⁡(1−0.2)=−0.2−(0.2)22−(0.2)33−⋯\ln 0.8 = \ln(1 - 0.2) = -0.2 - \frac{(0.2)^2}{2} - \frac{(0.2)^3}{3} - \cdots: every term is negative: NO. The check is on the series AT THE POINT, not on the function: the same ln⁡(1+x)\ln(1 + x) alternates at x=0.2x = 0.2 and not at x=−0.2x = -0.2.

Exercise 5: How many terms? The degree needed for a given accuracy

The question is now reversed: the accuracy is imposed, and the degree nn is the unknown. The method is always the same: write the bound as a function of nn, then find the smallest nn that makes it small enough. The bound, not the error, is what decides, because only the bound is known.

  • a) Find nn such that Tn(1)T_n(1) approximates ee to within 10−310^{-3}. Another student, asked for an error below 2×10−42 \times 10^{-4}, keeps the same T6(1)T_6(1) because the next term, 15040\frac{1}{5040}, is below 2×10−42 \times 10^{-4}: what is wrong?
  • b) How many nonzero terms of the series of sin⁡0.5\sin 0.5 guarantee an error below 10−610^{-6}?
  • c) Find the smallest degree nn for which Tn(0.5)T_n(0.5) of ln⁡(1+x)\ln(1 + x) approximates ln⁡1.5\ln 1.5 to within 0.010.01, and give that approximation.
  • d) Find a degree nn such that TnT_n of cos⁡x\cos x at 00 is within 10−410^{-4} of cos⁡x\cos x for EVERY xx in [−1,1][-1, 1].
  • e) Find a degree nn such that TnT_n of exe^x at 00 is within 0.010.01 of exe^x for EVERY xx in [0,2][0, 2], and compare with the degree needed on [0,1][0, 1].
Show the solution

Answers

  • a) 3(n+1)!<10−3\frac{3}{(n + 1)!} < 10^{-3} gives n=6n = 6, e≈1957720e \approx \frac{1957}{720}; the next-term rule is only valid for an ALTERNATING series, and e−T6(1)≈2.3×10−4>2×10−4e - T_6(1) \approx 2.3 \times 10^{-4} > 2 \times 10^{-4}.
  • b) Four: x−x36+x5120−x75040x - \frac{x^3}{6} + \frac{x^5}{120} - \frac{x^7}{5040}, since (0.5)99!≈5×10−9\frac{(0.5)^9}{9!} \approx 5 \times 10^{-9} while (0.5)77!≈1.6×10−6\frac{(0.5)^7}{7!} \approx 1.6 \times 10^{-6}.
  • c) n=4n = 4: ln⁡1.5≈77192\ln 1.5 \approx \frac{77}{192}, error below 1160\frac{1}{160}.
  • d) n=6n = 6 (or 77): error at most 18!=140320\frac{1}{8!} = \frac{1}{40320} on [−1,1][-1, 1].
  • e) On [0,2][0, 2]: 9⋅2n+1(n+1)!<0.01\frac{9 \cdot 2^{n+1}}{(n + 1)!} < 0.01 gives n=9n = 9; on [0,1][0, 1]: 3(n+1)!<0.01\frac{3}{(n + 1)!} < 0.01 gives n=5n = 5.

a) Taylor's inequality at x=1x = 1 with a=0a = 0: f(n+1)=ex≤e<3f^{(n+1)} = e^x \le e < 3 on [0,1][0, 1], so ∣Rn(1)∣≤3(n+1)!\lvert R_n(1)\rvert \le \frac{3}{(n + 1)!}. We need (n+1)!>3000(n + 1)! > 3000: 6!=7206! = 720 is too small, 7!=50407! = 5040 works, so n+1=7n + 1 = 7 and n=6n = 6. Then T6(1)=1+1+12+16+124+1120+1720=720+720+360+120+30+6+1720=1957720≈2.71806T_6(1) = 1 + 1 + \frac{1}{2} + \frac{1}{6} + \frac{1}{24} + \frac{1}{120} + \frac{1}{720} = \frac{720 + 720 + 360 + 120 + 30 + 6 + 1}{720} = \frac{1957}{720} \approx 2.71806. The second student's rule, stop when the next term is below the tolerance, is the alternating series estimate, and the series of e=e1e = e^1 does NOT alternate: every omitted term is positive and they ADD UP. The next term is 15040≈1.98×10−4\frac{1}{5040} \approx 1.98 \times 10^{-4}, but the tail after T6(1)T_6(1) is 15040+140320+⋯≈2.3×10−4\frac{1}{5040} + \frac{1}{40320} + \cdots \approx 2.3 \times 10^{-4}, above 2×10−42 \times 10^{-4}. The rule has to be earned by checking the hypotheses; here Taylor's inequality asks for (n+1)!>15 000(n + 1)! > 15\,000, so n=7n = 7.

b) At x=0.5x = 0.5 the sine series alternates with decreasing terms (0.5)2k+1(2k+1)!\frac{(0.5)^{2k+1}}{(2k + 1)!}, so the error is below the first omitted term. Try: (0.5)77!=1128⋅5040=1645 120≈1.6×10−6\frac{(0.5)^7}{7!} = \frac{1}{128 \cdot 5040} = \frac{1}{645\,120} \approx 1.6 \times 10^{-6}, too big; (0.5)99!=1512⋅362 880\frac{(0.5)^9}{9!} = \frac{1}{512 \cdot 362\,880}, about 5×10−95 \times 10^{-9}, small enough. So the first omitted term must be the one in x9x^9: keep x−x36+x5120−x75040x - \frac{x^3}{6} + \frac{x^5}{120} - \frac{x^7}{5040}, FOUR nonzero terms, which is T7=T8T_7 = T_8. Counting terms and counting the degree are two different things for the sine: say which one you are giving.

c) ln⁡(1.5)=∑k≥1(−1)k+1(0.5)kk\ln(1.5) = \sum_{k \ge 1} (-1)^{k+1}\frac{(0.5)^k}{k} alternates with terms (0.5)kk\frac{(0.5)^k}{k} decreasing to 00, so ∣ln⁡1.5−Tn(0.5)∣≤(0.5)n+1n+1\lvert \ln 1.5 - T_n(0.5)\rvert \le \frac{(0.5)^{n+1}}{n + 1}. For n=3n = 3: 116⋅4=164≈0.0156\frac{1}{16 \cdot 4} = \frac{1}{64} \approx 0.0156, too big. For n=4n = 4: 132⋅5=1160=0.00625<0.01\frac{1}{32 \cdot 5} = \frac{1}{160} = 0.00625 < 0.01. So n=4n = 4 and ln⁡1.5≈12−18+124−164=96−24+8−3192=77192≈0.401\ln 1.5 \approx \frac{1}{2} - \frac{1}{8} + \frac{1}{24} - \frac{1}{64} = \frac{96 - 24 + 8 - 3}{192} = \frac{77}{192} \approx 0.401, an underestimate since the first omitted term, +1160+\frac{1}{160}, is positive. Four terms for two decimals: the series of ln⁡(1+x)\ln(1 + x) is slow at x=0.5x = 0.5. Exercise 10 does much better.

d) The accuracy must hold for all xx in [−1,1][-1, 1] at once, so the bound must be taken at the WORST xx, here ∣x∣=1\lvert x\rvert = 1. For every such xx the cosine series alternates with decreasing terms x2k(2k)!\frac{x^{2k}}{(2k)!} (ratio x2(2k+1)(2k+2)<1\frac{x^2}{(2k + 1)(2k + 2)} < 1), so the error of the polynomial ending with the term in x2mx^{2m} is at most ∣x∣2m+2(2m+2)!≤1(2m+2)!\frac{\lvert x\rvert^{2m+2}}{(2m + 2)!} \le \frac{1}{(2m + 2)!}. Need (2m+2)!>104(2m + 2)! > 10^4: 6!=7206! = 720 no, 8!=403208! = 40320 yes. So stop after −x6720-\frac{x^6}{720}: T6(x)=1−x22+x424−x6720T_6(x) = 1 - \frac{x^2}{2} + \frac{x^4}{24} - \frac{x^6}{720}, error at most 140320≈2.5×10−5\frac{1}{40320} \approx 2.5 \times 10^{-5} on the whole interval (and T7=T6T_7 = T_6). Taylor's inequality gives the same with n=7n = 7 and M=1M = 1.

e) On [0,2][0, 2] the worst point is x=2x = 2 twice over: f(n+1)=ex≤e2<9f^{(n+1)} = e^x \le e^2 < 9 (since e<3e < 3), and ∣x∣n+1≤2n+1\lvert x\rvert^{n+1} \le 2^{n+1}. So ∣Rn(x)∣≤9⋅2n+1(n+1)!\lvert R_n(x)\rvert \le \frac{9 \cdot 2^{n+1}}{(n + 1)!} for all xx in [0,2][0, 2]. Try: n+1=8n + 1 = 8 gives 9⋅25640320≈0.057\frac{9 \cdot 256}{40320} \approx 0.057; n+1=9n + 1 = 9 gives 9⋅512362 880≈0.013\frac{9 \cdot 512}{362\,880} \approx 0.013, still too big; n+1=10n + 1 = 10 gives 9⋅10243 628 800≈0.0025\frac{9 \cdot 1024}{3\,628\,800} \approx 0.0025. So n=9n = 9. On [0,1][0, 1]: M=e<3M = e < 3 and 3(n+1)!<0.01\frac{3}{(n + 1)!} < 0.01 asks for (n+1)!>300(n + 1)! > 300, so 6!=7206! = 720 and n=5n = 5. Doubling the interval almost doubles the degree: both MM and ∣x∣n+1\lvert x\rvert^{n+1} grow, and the factorial has to catch up with 2n+12^{n+1} before the bound falls. It always does in the end, which is why the series of exe^x converges for every xx, but the price of distance is paid in degree. This is the lesson of Exercise 7 seen from the other side: a point far from the centre costs terms.

Part B: problems and reasoning (/50)

Exercise 6: The error band: on which interval is sin x close enough to x minus x cubed over 6?

So far the point xx was given and the error was bounded. Here the tolerance is given, 10−410^{-4}, and the question is: on which interval ∣x∣≤r\lvert x\rvert \le r does the approximation sin⁡x≈x−x36\sin x \approx x - \frac{x^3}{6} GUARANTEE it?

The figure shows, in units of 10−410^{-4}, three curves on [−0.6,0.6][-0.6, 0.6]: the lazy bound x424\frac{x^4}{24} (steep), the bound ∣x∣5120\frac{\lvert x\rvert^5}{120} (dashed), and the real error ∣sin⁡x−x+x36∣\lvert\sin x - x + \frac{x^3}{6}\rvert; the tolerance is the horizontal dashed line at 11.

-0.5-0.4-0.3-0.2-0.10.10.20.30.40.50.61234567x⁴/24|x|⁵/120 andthe real errortolerance× 10⁻⁴
  • a) Show that ∣sin⁡x−(x−x36)∣≤∣x∣5120\left\lvert\sin x - \left(x - \frac{x^3}{6}\right)\right\rvert \le \frac{\lvert x\rvert^5}{120} for EVERY real xx.
  • b) Deduce a simple value rr, with one decimal, such that the error is below 10−410^{-4} for all ∣x∣≤r\lvert x\rvert \le r.
  • c) Answer the same question with the bound x424\frac{x^4}{24} obtained from n=3n = 3. Which curve of the figure corresponds to which bound?
  • d) Read on the figure where the real error reaches 10−410^{-4}. What does this say about the bound of a)?
  • e) Show that x−x36<sin⁡x<xx - \frac{x^3}{6} < \sin x < x for 0<x≤10 < x \le 1, and convert the interval of b) to degrees.
Show the solution

Answers

  • a) T3=T4T_3 = T_4 and ∣f(5)∣=∣cos⁡x∣≤1\lvert f^{(5)}\rvert = \lvert\cos x\rvert \le 1 on all of R\mathbb{R}: ∣R4(x)∣≤∣x∣55!\lvert R_4(x)\rvert \le \frac{\lvert x\rvert^5}{5!}.
  • b) r=0.4r = 0.4: (0.4)5120=0.01024120<10−4\frac{(0.4)^5}{120} = \frac{0.01024}{120} < 10^{-4}, while r=0.5r = 0.5 is not guaranteed.
  • c) r=0.2r = 0.2 only; the steep red curve is x424\frac{x^4}{24}, the dashed one ∣x∣5120\frac{\lvert x\rvert^5}{120}.
  • d) Around ∣x∣≈0.41\lvert x\rvert \approx 0.41: the bound almost coincides with the real error, it is sharp.
  • e) Alternating estimate, signs of the first omitted terms; 0.40.4 rad ≈23∘\approx 23^\circ.

a) The sine has no x4x^4 term, so x−x36x - \frac{x^3}{6} is T3T_3 AND T4T_4, and the error is R4(x)R_4(x). Taylor's inequality with n=4n = 4 needs M≥∣f(5)(x)∣=∣cos⁡x∣M \ge \lvert f^{(5)}(x)\rvert = \lvert\cos x\rvert, and M=1M = 1 works on the whole real line, whatever the interval. So ∣R4(x)∣≤15!∣x∣5=∣x∣5120\lvert R_4(x)\rvert \le \frac{1}{5!}\lvert x\rvert^5 = \frac{\lvert x\rvert^5}{120} for every real xx. For ∣x∣≤1\lvert x\rvert \le 1 the alternating series estimate gives the same bound (first omitted term x5120\frac{x^5}{120}), but only Taylor's inequality gives it for ALL xx, where the terms of the series first grow before they decrease.

b) We need ∣x∣5120<10−4\frac{\lvert x\rvert^5}{120} < 10^{-4}, i.e. ∣x∣5<0.012\lvert x\rvert^5 < 0.012. By hand: (0.4)5=0.01024<0.012(0.4)^5 = 0.01024 < 0.012, and (0.5)5=132=0.03125>0.012(0.5)^5 = \frac{1}{32} = 0.03125 > 0.012. Since ∣x∣5\lvert x\rvert^5 increases with ∣x∣\lvert x\rvert, ∣x∣≤0.4\lvert x\rvert \le 0.4 gives ∣x∣5120≤0.01024120≈0.85×10−4<10−4\frac{\lvert x\rvert^5}{120} \le \frac{0.01024}{120} \approx 0.85 \times 10^{-4} < 10^{-4}: r=0.4r = 0.4 works. r=0.5r = 0.5 is not guaranteed by this bound. Note the direction of the reasoning: we look for the xx that make the BOUND small, because a small bound forces a small error; the converse is not needed.

c) With n=3n = 3, M≥∣f(4)∣=∣sin⁡x∣M \ge \lvert f^{(4)}\rvert = \lvert\sin x\rvert, M=1M = 1, and ∣R3(x)∣≤x424\lvert R_3(x)\rvert \le \frac{x^4}{24}. We need x4<0.0024x^4 < 0.0024: (0.2)4=0.0016(0.2)^4 = 0.0016 works, (0.3)4=0.0081(0.3)^4 = 0.0081 does not, so only r=0.2r = 0.2 is guaranteed, half of b). On the figure, the steep red curve is x424\frac{x^4}{24}: it crosses the tolerance line near 0.220.22 and leaves the window soon after. The dashed curve ∣x∣5120\frac{\lvert x\rvert^5}{120} crosses it near 0.410.41. The only difference between the two answers is whether one noticed that T3=T4T_3 = T_4.

d) The blue real error is hidden under the dashed bound: at this scale the two curves coincide, and the real error reaches 10−410^{-4} at about ∣x∣≈0.41\lvert x\rvert \approx 0.41. So the bound of a) is SHARP: the true error is the first omitted term minus much smaller ones, x5120−x75040+⋯\frac{x^5}{120} - \frac{x^7}{5040} + \cdots, and the answer r=0.4r = 0.4 is almost the best possible. The lazy bound, by contrast, gives away half of the interval. A good error bound is not only true, it is close to the truth, and this is decided by the choice of nn and MM, not by the arithmetic.

e) For 0<x≤10 < x \le 1 the series x−x36+x5120−⋯x - \frac{x^3}{6} + \frac{x^5}{120} - \cdots alternates, with terms x2k+1(2k+1)!\frac{x^{2k+1}}{(2k + 1)!} decreasing to 00. The error after the first term, sin⁡x−x\sin x - x, has the sign of the first omitted term −x36-\frac{x^3}{6}: negative, so sin⁡x<x\sin x < x. The error after two terms, sin⁡x−(x−x36)\sin x - \left(x - \frac{x^3}{6}\right), has the sign of +x5120+\frac{x^5}{120}: positive, so sin⁡x>x−x36\sin x > x - \frac{x^3}{6}. This is the pattern seen in Exercise 1: T1T_1 above, T3T_3 below. In degrees, 0.40.4 rad =0.4⋅180∘π≈72∘3.14≈23∘= 0.4 \cdot \frac{180^\circ}{\pi} \approx \frac{72^\circ}{3.14} \approx 23^\circ: from 0∘0^\circ to about 23∘23^\circ, two terms of the series give the sine to four decimals, which is how sine tables were once built.

Exercise 7: Centred away from zero: cos 31 degrees and the radian trap

A Taylor polynomial does not have to be centred at 00. To approximate ff at a point, centre it at the NEAREST point where ff and its derivatives are known exactly: the bound M(n+1)!∣x−a∣n+1\frac{M}{(n + 1)!}\lvert x - a\rvert^{n+1} then works with a small ∣x−a∣\lvert x - a\rvert.

Here the target is cos⁡31∘\cos 31^\circ, next to 30∘=π630^\circ = \frac{\pi}{6}, where cos⁡π6=32\cos\frac{\pi}{6} = \frac{\sqrt{3}}{2} and sin⁡π6=12\sin\frac{\pi}{6} = \frac{1}{2}.

  • a) Compute T2T_2 of cos⁡x\cos x at a=π6a = \frac{\pi}{6}.
  • b) Express 31∘31^\circ in radians as π6+h\frac{\pi}{6} + h and deduce an exact expression approximating cos⁡31∘\cos 31^\circ. What happens if one takes h=1h = 1?
  • c) Bound the error with Taylor's inequality, using π<3.6\pi < 3.6 to make the bound a simple fraction.
  • d) Is the approximation too large or too small? Give an interval that contains cos⁡31∘\cos 31^\circ.
  • e) Estimate the bound one would get with T2T_2 of cos⁡x\cos x at 00, and conclude on the choice of the centre.
Show the solution

Answers

  • a) T2(x)=32−12(x−π6)−34(x−π6)2T_2(x) = \frac{\sqrt{3}}{2} - \frac{1}{2}\left(x - \frac{\pi}{6}\right) - \frac{\sqrt{3}}{4}\left(x - \frac{\pi}{6}\right)^2
  • b) h=π180h = \frac{\pi}{180}: cos⁡31∘≈32−π360−3 π2129 600≈0.85717\cos 31^\circ \approx \frac{\sqrt{3}}{2} - \frac{\pi}{360} - \frac{\sqrt{3}\,\pi^2}{129\,600} \approx 0.85717; h=1h = 1 gives a negative value, absurd.
  • c) ∣R2∣≤16(π180)3<(0.02)36=1750 000\lvert R_2\rvert \le \frac{1}{6}\left(\frac{\pi}{180}\right)^3 < \frac{(0.02)^3}{6} = \frac{1}{750\,000}
  • d) Too small: T2<cos⁡31∘<T2+1750 000T_2 < \cos 31^\circ < T_2 + \frac{1}{750\,000}.
  • e) About (0.54)424≈0.0036\frac{(0.54)^4}{24} \approx 0.0036 at 00: some two thousand times worse; centre at the nearest known point.

a) f(x)=cos⁡xf(x) = \cos x, f′(x)=−sin⁡xf'(x) = -\sin x, f′′(x)=−cos⁡xf''(x) = -\cos x. At π6\frac{\pi}{6}: f=32f = \frac{\sqrt{3}}{2}, f′=−12f' = -\frac{1}{2}, f′′=−32f'' = -\frac{\sqrt{3}}{2}. So T2(x)=32−12(x−π6)−32⋅2!(x−π6)2=32−12(x−π6)−34(x−π6)2T_2(x) = \frac{\sqrt{3}}{2} - \frac{1}{2}\left(x - \frac{\pi}{6}\right) - \frac{\sqrt{3}}{2 \cdot 2!}\left(x - \frac{\pi}{6}\right)^2 = \frac{\sqrt{3}}{2} - \frac{1}{2}\left(x - \frac{\pi}{6}\right) - \frac{\sqrt{3}}{4}\left(x - \frac{\pi}{6}\right)^2. The powers stay in x−π6x - \frac{\pi}{6}: expanding them in powers of xx loses the whole point of the centre.

b) 31∘=30∘+1∘=π6+π18031^\circ = 30^\circ + 1^\circ = \frac{\pi}{6} + \frac{\pi}{180}, so h=π180h = \frac{\pi}{180}. Then cos⁡31∘≈T2(π6+h)=32−h2−34h2=32−π360−3 π24⋅32 400=32−π360−3 π2129 600\cos 31^\circ \approx T_2\left(\frac{\pi}{6} + h\right) = \frac{\sqrt{3}}{2} - \frac{h}{2} - \frac{\sqrt{3}}{4}h^2 = \frac{\sqrt{3}}{2} - \frac{\pi}{360} - \frac{\sqrt{3}\,\pi^2}{4 \cdot 32\,400} = \frac{\sqrt{3}}{2} - \frac{\pi}{360} - \frac{\sqrt{3}\,\pi^2}{129\,600}. This exact expression is the answer; an order of magnitude from 3≈1.732\sqrt{3} \approx 1.732 and π≈3.1416\pi \approx 3.1416: 0.86603−0.00873−0.00013≈0.857170.86603 - 0.00873 - 0.00013 \approx 0.85717. With h=1h = 1, as if one degree were one unit: 32−12−34≈0.866−0.5−0.433<0\frac{\sqrt{3}}{2} - \frac{1}{2} - \frac{\sqrt{3}}{4} \approx 0.866 - 0.5 - 0.433 < 0, a negative cosine for an acute angle. Every formula of calculus for sin⁡\sin and cos⁡\cos, and therefore every Taylor polynomial, is written in RADIANS: ddxsin⁡x=cos⁡x\frac{d}{dx}\sin x = \cos x is false in degrees.

c) n=2n = 2: we need M≥∣f′′′(x)∣=∣sin⁡x∣M \ge \lvert f'''(x)\rvert = \lvert\sin x\rvert between π6\frac{\pi}{6} and 31∘31^\circ, and M=1M = 1 is valid everywhere. So ∣R2∣≤13!(π180)3\lvert R_2\rvert \le \frac{1}{3!}\left(\frac{\pi}{180}\right)^3. With π<3.6\pi < 3.6, π180<3.6180=0.02\frac{\pi}{180} < \frac{3.6}{180} = 0.02, and ∣R2∣<(0.02)36=8×10−66=1750 000≈1.3×10−6\lvert R_2\rvert < \frac{(0.02)^3}{6} = \frac{8 \times 10^{-6}}{6} = \frac{1}{750\,000} \approx 1.3 \times 10^{-6}. A sharper MM is available, sin⁡x≤sin⁡31∘<sin⁡45∘<0.71\sin x \le \sin 31^\circ < \sin 45^\circ < 0.71 on the interval, which cuts the bound by almost a third; it is not needed to get five decimals.

d) The Lagrange form of the remainder is R2=f′′′(z)3!h3=sin⁡z6h3R_2 = \frac{f'''(z)}{3!}h^3 = \frac{\sin z}{6}h^3 for some zz between π6\frac{\pi}{6} and 31∘31^\circ. There sin⁡z>0\sin z > 0 and h>0h > 0, so R2>0R_2 > 0: cos⁡31∘\cos 31^\circ is LARGER than T2T_2, which is an underestimate. Hence T2<cos⁡31∘<T2+1750 000T_2 < \cos 31^\circ < T_2 + \frac{1}{750\,000}, with T2=32−π360−3 π2129 600T_2 = \frac{\sqrt{3}}{2} - \frac{\pi}{360} - \frac{\sqrt{3}\,\pi^2}{129\,600}. (A machine gives an error of about 4.5×10−74.5 \times 10^{-7}, positive, inside the interval.) The alternating estimate would NOT give the sign here: at a=π6a = \frac{\pi}{6} the signs of the terms go +,−,−,+,+,…+, -, -, +, +, \dots, in pairs, and the series does not alternate.

e) Centred at 00, the same degree uses x=31π180≈0.54x = \frac{31\pi}{180} \approx 0.54. Since T2=T3T_2 = T_3 for the cosine at 00, the best bound is x424\frac{x^4}{24}, about 0.08524≈0.0036\frac{0.085}{24} \approx 0.0036, against 1.3×10−61.3 \times 10^{-6} at π6\frac{\pi}{6}: roughly two to three thousand times worse, with the same effort. The bound grows like ∣x−a∣n+1\lvert x - a\rvert^{n+1}, so the distance to the centre is raised to a power: halving it gains a factor 2n+12^{n+1}, and here the distance was divided by thirty. Choose the centre first, the degree second.

Exercise 8: Five statements to correct

Each statement below was written on a MATH 141 practice paper, and each one is false or unjustified. Say what is wrong, give the correct statement, and settle it with a short computation or a counterexample.

  • a) For f(x)=11−xf(x) = \frac{1}{1 - x} and 0≤x≤0.50 \le x \le 0.5, T2(x)=1+x+x2T_2(x) = 1 + x + x^2 and M=f′′′(0)=6M = f'''(0) = 6, so ∣R2(x)∣≤63!(0.5)3=18\lvert R_2(x)\rvert \le \frac{6}{3!}(0.5)^3 = \frac{1}{8}.
  • b) The terms of ∑1k!\sum\frac{1}{k!} decrease, so e−T3(1)e - T_3(1) is at most the first omitted term, 124\frac{1}{24}.
  • c) Taylor's inequality with n=3n = 3 bounds the error of sin⁡0.1≈0.1−(0.1)36\sin 0.1 \approx 0.1 - \frac{(0.1)^3}{6} by (0.1)424≈4×10−6\frac{(0.1)^4}{24} \approx 4 \times 10^{-6}, so T3T_3 cannot give sin⁡0.1\sin 0.1 to within 10−610^{-6}.
  • d) On [0,0.5][0, 0.5], M=e0.5<2M = e^{0.5} < 2 bounds f′′′(x)f'''(x) for f(x)=exf(x) = e^x, so ∣ex−(1+x+x22)∣≤2x36=x33\left\lvert e^x - \left(1 + x + \frac{x^2}{2}\right)\right\rvert \le \frac{2x^3}{6} = \frac{x^3}{3} for every x≥0x \ge 0.
  • e) e0.2≈1.22133e^{0.2} \approx 1.22133 with an error below 10−410^{-4}, so the first four decimals of e0.2e^{0.2} are 1.22131.2213.
Show the solution

Answers

  • a) False: f′′′=6(1−x)4f''' = \frac{6}{(1 - x)^4} is largest at x=0.5x = 0.5, M=96M = 96, bound 22; the true error at 0.50.5 is 14>18\frac{1}{4} > \frac{1}{8}.
  • b) False: the series does not alternate; e−83≈0.052>124e - \frac{8}{3} \approx 0.052 > \frac{1}{24}. Taylor with M=3M = 3 gives 18\frac{1}{8}.
  • c) False: T3=T4T_3 = T_4, so ∣R4∣≤(0.1)5120≈8×10−8<10−6\lvert R_4\rvert \le \frac{(0.1)^5}{120} \approx 8 \times 10^{-8} < 10^{-6}.
  • d) False: MM holds on [0,0.5][0, 0.5] only; at x=3x = 3 the error e3−172>11e^3 - \frac{17}{2} > 11 exceeds 273=9\frac{27}{3} = 9.
  • e) False: the bound gives 1.22133<e0.2<1.221421.22133 < e^{0.2} < 1.22142, and in fact e0.2=1.22140…e^{0.2} = 1.22140\ldots: only 1.2211.221 is certain.

a) FALSE, MM was taken at the centre. f′′′(x)=6(1−x)4f'''(x) = \frac{6}{(1 - x)^4} is INCREASING on [0,0.5][0, 0.5], so its maximum is at x=0.5x = 0.5: M=6(1/2)4=96M = \frac{6}{(1/2)^4} = 96, and Taylor's inequality gives ∣R2(x)∣≤966(0.5)3=2\lvert R_2(x)\rvert \le \frac{96}{6}(0.5)^3 = 2. The claimed 18\frac{1}{8} is violated by the function itself: f(0.5)=2f(0.5) = 2 and T2(0.5)=1+0.5+0.25=1.75T_2(0.5) = 1 + 0.5 + 0.25 = 1.75, so the true error is 14\frac{1}{4}. In fact the remainder is known exactly here, since 11−x−(1+x+x2)=x31−x\frac{1}{1 - x} - (1 + x + x^2) = \frac{x^3}{1 - x}, which is 14\frac{1}{4} at x=0.5x = 0.5 and within the correct bound 22. Correct statement: ∣R2(x)∣≤2\lvert R_2(x)\rvert \le 2 on [0,0.5][0, 0.5], with M=96M = 96 at the worst point.

b) FALSE, the first-omitted-term rule is the alternating series estimate, and ∑1k!\sum\frac{1}{k!} has only positive terms. Decreasing terms are not enough: the omitted terms all push in the same direction and add up. Indeed T3(1)=1+1+12+16=83T_3(1) = 1 + 1 + \frac{1}{2} + \frac{1}{6} = \frac{8}{3} and e−83≈2.7183−2.6667=0.0516>124≈0.0417e - \frac{8}{3} \approx 2.7183 - 2.6667 = 0.0516 > \frac{1}{24} \approx 0.0417. Correct statement: by Taylor's inequality with M=e<3M = e < 3 on [0,1][0, 1], 0<e−T3(1)≤34!=180 < e - T_3(1) \le \frac{3}{4!} = \frac{1}{8}.

c) FALSE, the conclusion does not follow. The bound (0.1)424\frac{(0.1)^4}{24} is true but it is an upper bound: a large bound does not prove a large error. And a better bound exists: the sine has no x4x^4 term, so T3=T4T_3 = T_4 and, with ∣f(5)∣=∣cos⁡x∣≤1\lvert f^{(5)}\rvert = \lvert\cos x\rvert \le 1, ∣R4(0.1)∣≤(0.1)5120=112 000 000<10−6\lvert R_4(0.1)\rvert \le \frac{(0.1)^5}{120} = \frac{1}{12\,000\,000} < 10^{-6}. Correct statement: T3(0.1)=5996000T_3(0.1) = \frac{599}{6000} gives sin⁡0.1\sin 0.1 to within about 8.3×10−88.3 \times 10^{-8}.

d) FALSE, the bound was proved on [0,0.5][0, 0.5] and used outside it. M=2M = 2 bounds f′′′=exf''' = e^x only for x≤0.5x \le 0.5; beyond, the exponential passes 22 and keeps growing. Counterexample x=3x = 3: T2(3)=1+3+92=172T_2(3) = 1 + 3 + \frac{9}{2} = \frac{17}{2}, and e3>(2.7)3=19.683e^3 > (2.7)^3 = 19.683, so the true error is above 1111, while the claimed bound gives 273=9\frac{27}{3} = 9. Correct statement: on [0,d][0, d], M=edM = e^d, and ∣R2(x)∣≤edx36\lvert R_2(x)\rvert \le \frac{e^d x^3}{6} for 0≤x≤d0 \le x \le d. A Taylor bound is a statement about ONE interval; a new interval needs a new MM, found again at its worst point.

e) FALSE, an error bound gives an INTERVAL, not digits. From Exercise 3, T3(0.2)=458375=1.221333…T_3(0.2) = \frac{458}{375} = 1.221333\ldots and 0<e0.2−T3(0.2)<1120000 < e^{0.2} - T_3(0.2) < \frac{1}{12000}, so 1.22133<e0.2<1.221421.22133 < e^{0.2} < 1.22142. That interval contains numbers beginning with 1.22131.2213 AND with 1.22141.2214, so the fourth decimal is not decided; and in fact e0.2=1.22140…e^{0.2} = 1.22140\ldots The error is below 10−410^{-4} while the fourth decimal of the approximation is wrong. Correct statement: e0.2∈(1.22133,1.22142)e^{0.2} \in (1.22133, 1.22142), so the digits 1.2211.221 are certain, and to four decimals e0.2e^{0.2} rounds to 1.22141.2214.

Exercise 9: Physics runs on Taylor polynomials: the pendulum, the Lorentz factor and a GPS clock

Two approximations are used in every physics course without comment. For a pendulum, sin⁡θ≈θ\sin\theta \approx \theta turns the equation of motion into that of a harmonic oscillator. In special relativity, the Lorentz factor γ=11−β2\gamma = \frac{1}{\sqrt{1 - \beta^2}}, with β=vc\beta = \frac{v}{c}, is replaced by 1+β221 + \frac{\beta^2}{2} at everyday speeds. Both are Taylor polynomials, and an error bound says exactly when they may be trusted.

The figure shows γ\gamma and 1+β221 + \frac{\beta^2}{2} for 0≤β≤0.90 \le \beta \le 0.9. Use c=3×105c = 3 \times 10^5 km/s. No calculator.

0.10.20.30.40.50.60.70.80.911.21.41.61.822.22.4γ = 1/√(1 − β²)1 + β²/2β = v/c
  • a) Show that for 0<θ≤10 < \theta \le 1 the relative error of sin⁡θ≈θ\sin\theta \approx \theta, namely θ−sin⁡θsin⁡θ\frac{\theta - \sin\theta}{\sin\theta}, is at most θ26−θ2\frac{\theta^2}{6 - \theta^2}. Deduce an amplitude, in radians and in degrees, below which it is under 11 percent.
  • b) With u=β2u = \beta^2, compute T1T_1 of g(u)=(1−u)−1/2g(u) = (1 - u)^{-1/2} at 00. Deduce the approximation of γ\gamma and show that the relativistic kinetic energy (γ−1)mc2(\gamma - 1)mc^2 becomes 12mv2\frac{1}{2}mv^2.
  • c) For v≤0.1cv \le 0.1c, bound the error of γ≈1+β22\gamma \approx 1 + \frac{\beta^2}{2} and give its sign.
  • d) Deduce that for v≤0.1cv \le 0.1c the kinetic energy 12mv2\frac{1}{2}mv^2 is within 11 percent of (γ−1)mc2(\gamma - 1)mc^2.
  • e) A GPS satellite moves at about 3.93.9 km/s. Its clock runs slow by the fraction γ−1\gamma - 1. Estimate the delay accumulated in one day (86 40086\,400 s), and say whether the approximation of b) is good enough for it.
Show the solution

Answers

  • a) θ−sin⁡θ≤θ36\theta - \sin\theta \le \frac{\theta^3}{6} and sin⁡θ≥θ−θ36\sin\theta \ge \theta - \frac{\theta^3}{6}; under 11 percent for θ≤0.24\theta \le 0.24 rad, about 14∘14^\circ.
  • b) g(u)≈1+u2g(u) \approx 1 + \frac{u}{2}, so γ≈1+β22\gamma \approx 1 + \frac{\beta^2}{2} and (γ−1)mc2≈12mv2(\gamma - 1)mc^2 \approx \frac{1}{2}mv^2.
  • c) M=34(0.99)−5/2<0.78M = \frac{3}{4}(0.99)^{-5/2} < 0.78: 0<γ−1−β22≤0.78⋅(0.01)22=3.9×10−50 < \gamma - 1 - \frac{\beta^2}{2} \le 0.78 \cdot \frac{(0.01)^2}{2} = 3.9 \times 10^{-5}, an underestimate.
  • d) Relative error at most Mu≤0.78×0.01<1Mu \le 0.78 \times 0.01 < 1 percent.
  • e) β≈1.3×10−5\beta \approx 1.3 \times 10^{-5}, γ−1≈8.45×10−11\gamma - 1 \approx 8.45 \times 10^{-11}, about 77 microseconds per day; relative error of the approximation below 10−910^{-9}.

a) For 0<θ≤10 < \theta \le 1 the series θ−θ36+θ5120−⋯\theta - \frac{\theta^3}{6} + \frac{\theta^5}{120} - \cdots alternates with decreasing terms, so θ−θ36<sin⁡θ<θ\theta - \frac{\theta^3}{6} < \sin\theta < \theta (Exercise 6 e)). Hence 0<θ−sin⁡θ<θ360 < \theta - \sin\theta < \frac{\theta^3}{6} and sin⁡θ>θ−θ36=θ(6−θ2)6\sin\theta > \theta - \frac{\theta^3}{6} = \frac{\theta(6 - \theta^2)}{6}. Dividing: θ−sin⁡θsin⁡θ<θ3/6θ(6−θ2)/6=θ26−θ2\frac{\theta - \sin\theta}{\sin\theta} < \frac{\theta^3/6}{\theta(6 - \theta^2)/6} = \frac{\theta^2}{6 - \theta^2}. For 11 percent we need θ26−θ2≤0.01\frac{\theta^2}{6 - \theta^2} \le 0.01. Try θ=0.24\theta = 0.24: θ2=0.0576\theta^2 = 0.0576 and 0.05765.9424<0.05765.76=0.01\frac{0.0576}{5.9424} < \frac{0.0576}{5.76} = 0.01. So below θ=0.24\theta = 0.24 rad, that is 0.24⋅180∘π≈14∘0.24 \cdot \frac{180^\circ}{\pi} \approx 14^\circ, the small-angle approximation errs by less than 11 percent. This is where the usual rule of thumb, small angles under about fifteen degrees, comes from.

b) g(u)=(1−u)−1/2g(u) = (1 - u)^{-1/2}, g′(u)=12(1−u)−3/2g'(u) = \frac{1}{2}(1 - u)^{-3/2}, so g(0)=1g(0) = 1, g′(0)=12g'(0) = \frac{1}{2} and T1(u)=1+u2T_1(u) = 1 + \frac{u}{2}, the start of the binomial series with k=−12k = -\frac{1}{2}. With u=β2u = \beta^2: γ≈1+β22\gamma \approx 1 + \frac{\beta^2}{2}. Then (γ−1)mc2≈β22mc2=12mv2c2c2=12mv2(\gamma - 1)mc^2 \approx \frac{\beta^2}{2}mc^2 = \frac{1}{2}m\frac{v^2}{c^2}c^2 = \frac{1}{2}mv^2: Newton's kinetic energy is the first Taylor polynomial of Einstein's. The figure shows the two curves together up to β≈0.3\beta \approx 0.3, and separating fast after; γ\gamma blows up at β=1\beta = 1, the polynomial does not.

c) v≤0.1cv \le 0.1c means u=β2≤0.01u = \beta^2 \le 0.01. Taylor's inequality with n=1n = 1 needs M≥g′′(u)=34(1−u)−5/2M \ge g''(u) = \frac{3}{4}(1 - u)^{-5/2} on [0,0.01][0, 0.01]; g′′g'' is INCREASING in uu, so the worst point is u=0.01u = 0.01: M=34(0.99)−5/2M = \frac{3}{4}(0.99)^{-5/2}. By hand: (0.99)5/2>(0.99)3=0.970299>0.97(0.99)^{5/2} > (0.99)^3 = 0.970299 > 0.97, so M<0.750.97<0.78M < \frac{0.75}{0.97} < 0.78. Then ∣R1∣≤0.782(0.01)2=3.9×10−5\lvert R_1\rvert \le \frac{0.78}{2}(0.01)^2 = 3.9 \times 10^{-5}. Sign: R1=g′′(z)2u2>0R_1 = \frac{g''(z)}{2}u^2 > 0, so 1+β221 + \frac{\beta^2}{2} UNDERESTIMATES γ\gamma, as the figure shows: the orange curve is below the blue one everywhere. At β=0.1\beta = 0.1 exactly, γ=10.99≈1.0050378\gamma = \frac{1}{\sqrt{0.99}} \approx 1.0050378 against 1.0051.005: an error of 3.8×10−53.8 \times 10^{-5}, just under the bound.

d) The true kinetic energy is (γ−1)mc2(\gamma - 1)mc^2 and the approximation u2mc2\frac{u}{2}mc^2; the relative error is (γ−1)−u/2γ−1=R1γ−1\frac{(\gamma - 1) - u/2}{\gamma - 1} = \frac{R_1}{\gamma - 1}. Since R1>0R_1 > 0, γ−1>u2\gamma - 1 > \frac{u}{2}, and so R1γ−1<Mu2/2u/2=Mu≤0.78×0.01=0.0078\frac{R_1}{\gamma - 1} < \frac{Mu^2/2}{u/2} = Mu \le 0.78 \times 0.01 = 0.0078. Below 11 percent for every speed up to 0.1c0.1c, that is 30 00030\,000 km/s: Newtonian mechanics is not wrong at everyday speeds, it is a Taylor polynomial with a known, tiny error.

e) β=3.93×105=1.3×10−5\beta = \frac{3.9}{3 \times 10^5} = 1.3 \times 10^{-5}, so β2=1.69×10−10\beta^2 = 1.69 \times 10^{-10} and γ−1≈β22=8.45×10−11\gamma - 1 \approx \frac{\beta^2}{2} = 8.45 \times 10^{-11}. Over a day: 86 400×8.45×10−11=8.64×8.45×10−7≈7.3×10−686\,400 \times 8.45 \times 10^{-11} = 8.64 \times 8.45 \times 10^{-7} \approx 7.3 \times 10^{-6} s, about 77 microseconds, the value quoted for the special-relativity correction of GPS clocks (gravity adds a larger correction of the opposite sign, which is another story). By d), the relative error of the approximation is at most Mu≈0.75×1.7×10−10Mu \approx 0.75 \times 1.7 \times 10^{-10}, below 10−910^{-9}: the Taylor polynomial is far more accurate than the 3.93.9 km/s it is fed. Light travels 300300 metres in a microsecond, which is why a navigation system cannot ignore these seven.

Exercise 10: A final exam problem: ln 2 to six decimals with six terms

The alternating harmonic series 1−12+13−⋯1 - \frac{1}{2} + \frac{1}{3} - \cdots converges to ln⁡2\ln 2, but its first omitted term after nn terms is 1n+1\frac{1}{n + 1}: about a million terms for an error below 10−610^{-6}. The series of ln⁡(1+x)\ln(1 + x) is used there at x=1x = 1, the edge of its interval of convergence. This problem shows how a MATH 141 final expects you to do better: move the argument close to 00, then bound the tail with the right tool.

  • a) From the Maclaurin series of ln⁡(1+x)\ln(1 + x) and ln⁡(1−x)\ln(1 - x), show that ln⁡1+x1−x=2(x+x33+x55+⋯ )\ln\frac{1 + x}{1 - x} = 2\left(x + \frac{x^3}{3} + \frac{x^5}{5} + \cdots\right) for ∣x∣<1\lvert x\rvert < 1. Which xx gives ln⁡2\ln 2?
  • b) Approximate ln⁡2\ln 2 with the first three terms of this series, as a fraction.
  • c) Explain why neither the alternating series estimate nor a simple use of Taylor's inequality is convenient here, then bound the error by comparing the tail with a geometric series.
  • d) How many terms guarantee an error below 10−610^{-6}?
  • e) Use the same series with 1+x1−x=32\frac{1 + x}{1 - x} = \frac{3}{2} to approximate ln⁡32\ln\frac{3}{2} with two terms and a bound, then deduce ln⁡3\ln 3 with a guaranteed bound.
Show the solution

Answers

  • a) The even powers cancel, the odd ones double; 1+x1−x=2\frac{1 + x}{1 - x} = 2 for x=13x = \frac{1}{3}.
  • b) ln⁡2≈2(13+181+11215)=8421215≈0.69300\ln 2 \approx 2\left(\frac{1}{3} + \frac{1}{81} + \frac{1}{1215}\right) = \frac{842}{1215} \approx 0.69300
  • c) All terms positive, and the derivatives of ln⁡1+x1−x\ln\frac{1 + x}{1 - x} are unwieldy; tail ≤27⋅(1/3)71−1/9=16804\le \frac{2}{7} \cdot \frac{(1/3)^7}{1 - 1/9} = \frac{1}{6804}, so 8421215<ln⁡2<8421215+16804\frac{842}{1215} < \ln 2 < \frac{842}{1215} + \frac{1}{6804}.
  • d) Six terms, up to x1111\frac{x^{11}}{11}: tail ≤213⋅98⋅3−13≈1.1×10−7\le \frac{2}{13} \cdot \frac{9}{8} \cdot 3^{-13} \approx 1.1 \times 10^{-7}; five terms leave about 1.15×10−61.15 \times 10^{-6}.
  • e) x=15x = \frac{1}{5}: ln⁡32≈152375\ln\frac{3}{2} \approx \frac{152}{375}, error below 17500\frac{1}{7500}; ln⁡3≈8421215+152375\ln 3 \approx \frac{842}{1215} + \frac{152}{375}, error below 16804+17500<3×10−4\frac{1}{6804} + \frac{1}{7500} < 3 \times 10^{-4}.

a) For ∣x∣<1\lvert x\rvert < 1: ln⁡(1+x)=x−x22+x33−x44+⋯\ln(1 + x) = x - \frac{x^2}{2} + \frac{x^3}{3} - \frac{x^4}{4} + \cdots and, replacing xx by −x-x, ln⁡(1−x)=−x−x22−x33−x44−⋯\ln(1 - x) = -x - \frac{x^2}{2} - \frac{x^3}{3} - \frac{x^4}{4} - \cdots Subtracting, the even powers cancel and the odd ones double: ln⁡1+x1−x=ln⁡(1+x)−ln⁡(1−x)=2(x+x33+x55+⋯ )=2∑k≥0x2k+12k+1\ln\frac{1 + x}{1 - x} = \ln(1 + x) - \ln(1 - x) = 2\left(x + \frac{x^3}{3} + \frac{x^5}{5} + \cdots\right) = 2\sum_{k \ge 0}\frac{x^{2k+1}}{2k + 1}. Then 1+x1−x=2\frac{1 + x}{1 - x} = 2 gives 1+x=2−2x1 + x = 2 - 2x, x=13x = \frac{1}{3}: the argument is now 13\frac{1}{3} instead of 11, and its odd powers shrink by a factor 99 at each step.

b) 2(13+(1/3)33+(1/3)55)=2(13+181+11215)2\left(\frac{1}{3} + \frac{(1/3)^3}{3} + \frac{(1/3)^5}{5}\right) = 2\left(\frac{1}{3} + \frac{1}{81} + \frac{1}{1215}\right). With the common denominator 1215=5⋅2431215 = 5 \cdot 243: 405+15+11215=4211215\frac{405 + 15 + 1}{1215} = \frac{421}{1215}, so ln⁡2≈8421215≈0.69300\ln 2 \approx \frac{842}{1215} \approx 0.69300.

c) All the terms are positive, so the series does not alternate and the first omitted term is NOT a bound (Exercise 8 b)). Taylor's inequality would require bounding the seventh derivative of ln⁡1+x1−x\ln\frac{1 + x}{1 - x} on [0,13][0, \frac{1}{3}], possible but heavy. The tail itself is easy to bound: for k≥3k \ge 3, 12k+1≤17\frac{1}{2k + 1} \le \frac{1}{7}, so 2∑k≥3x2k+12k+1≤27∑k≥3x2k+1=27⋅x71−x22\sum_{k \ge 3}\frac{x^{2k+1}}{2k + 1} \le \frac{2}{7}\sum_{k \ge 3}x^{2k+1} = \frac{2}{7} \cdot \frac{x^7}{1 - x^2}, a geometric series of first term x7x^7 and ratio x2x^2. At x=13x = \frac{1}{3}: 27⋅12187⋅98=18122 472=16804≈1.5×10−4\frac{2}{7} \cdot \frac{1}{2187} \cdot \frac{9}{8} = \frac{18}{122\,472} = \frac{1}{6804} \approx 1.5 \times 10^{-4}. The tail is positive, so 8421215<ln⁡2<8421215+16804\frac{842}{1215} < \ln 2 < \frac{842}{1215} + \frac{1}{6804}. Three terms, three correct decimals, and a guarantee; the true error, about 1.43×10−41.43 \times 10^{-4}, is just under the bound.

d) Keeping the terms up to x2m−12m−1\frac{x^{2m-1}}{2m - 1}, the same comparison bounds the tail by 22m+1⋅x2m+11−x2=22m+1⋅98⋅3−(2m+1)\frac{2}{2m + 1} \cdot \frac{x^{2m+1}}{1 - x^2} = \frac{2}{2m + 1} \cdot \frac{9}{8} \cdot 3^{-(2m+1)}. First omitted power x11x^{11} (five terms kept): 211⋅98⋅1177 147≈1.15×10−6\frac{2}{11} \cdot \frac{9}{8} \cdot \frac{1}{177\,147} \approx 1.15 \times 10^{-6}, not enough. First omitted power x13x^{13} (six terms kept, up to x1111\frac{x^{11}}{11}): 213⋅98⋅11 594 323≈1.1×10−7\frac{2}{13} \cdot \frac{9}{8} \cdot \frac{1}{1\,594\,323} \approx 1.1 \times 10^{-7}, enough. Six terms against a million: the speed of a power series is decided by the size of xx, and choosing the representation that makes xx small is part of the answer.

e) 1+x1−x=32\frac{1 + x}{1 - x} = \frac{3}{2} gives 2+2x=3−3x2 + 2x = 3 - 3x, x=15x = \frac{1}{5}. Two terms: 2(15+1375)=2⋅76375=152375≈0.405332\left(\frac{1}{5} + \frac{1}{375}\right) = 2 \cdot \frac{76}{375} = \frac{152}{375} \approx 0.40533. Tail: 25⋅(1/5)51−1/25=25⋅13125⋅2524=17500≈1.3×10−4\frac{2}{5} \cdot \frac{(1/5)^5}{1 - 1/25} = \frac{2}{5} \cdot \frac{1}{3125} \cdot \frac{25}{24} = \frac{1}{7500} \approx 1.3 \times 10^{-4}, positive. Compare Exercise 5 c), where four terms of ln⁡(1+x)\ln(1 + x) at x=12x = \frac{1}{2} gave ln⁡32\ln\frac{3}{2} only to within 1160\frac{1}{160}. Then ln⁡3=ln⁡2+ln⁡32\ln 3 = \ln 2 + \ln\frac{3}{2}. With S=8421215+152375≈0.69300+0.40533=1.09834S = \frac{842}{1215} + \frac{152}{375} \approx 0.69300 + 0.40533 = 1.09834, both errors are positive, so S<ln⁡3<S+16804+17500S < \ln 3 < S + \frac{1}{6804} + \frac{1}{7500}, a guaranteed error below 3×10−43 \times 10^{-4}: 1.09833<ln⁡3<1.098621.09833 < \ln 3 < 1.09862. Errors ADD when approximations are added: the bound of a sum is the sum of the bounds.

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