M Mathematics Notes← Browse the course libraryOriginal PDF ↗
ANALYSIS

Calculus II

Integrals, differential equations and infinite series.
A browser-readable edition of MATH 138.

INSTRUCTORRobert Andre
SOURCE SIGNATUREbh2smith@gmail.com
TERMWinter 2004

Reading edition · Original wording retained, including known source typos; see conversion notes. Some typography and page layout differ; consult the PDF for the authoritative typeset version.

MATH 138 - Calculus II
bh2smith@gmail.com

These notes are based on a course by Robert Andre (Winter 2004). All errors are responsibility of the author.

1 Review

A few useful identities involving summation notation

  1. ∑i=1ni=1+2+3+…+n=(n+1)+(n+1)+…+(n+1)⏟n/2 times=n(n+1)2\sum_{i=1}^n i = 1+ 2 + 3+ \dots + n = \underbrace{(n+1)+(n+1) + \dots + (n+1)}_{n/2 \text{ times}} = \frac{n(n+1)}{2}

  2. ∑i=1ni2=n(n+1)(2n+1)6\sum_{i=1}^n i^2 = \frac{n(n+1)(2n+1)}{6}

  3. ∑i=1ni3=n2(n+1)24\sum_{i=1}^ni^3 = \frac{n^2(n+1)^2}{4}

    We call ii the index of summation.

  4. Let f(x)=2+3x2f(x) = 2+3x^2, then ∑i=24f(i)=∑i=24(2+3i2)=2+3(2)2+2+3(3)2+2+3(4)2=93\sum_{i=2}^4 f(i) = \sum_{i=2}^4 (2+3i^2) = 2+ 3(2)^2 + 2+ 3(3)^2 + 2+ 3(4)^2 = 93

  5. Geometric series:∑i=0n−1ari=a+ar+ar2+…+arn−1=a(1−rn)1−r\sum_{i=0}^{n-1} ar^i = a + ar + ar^2 + \dots + ar^{n-1} = \frac{a(1-r^n)}{1-r}

  6. Reindexing: ∑i=15(−1)i+1i2=∑i=04(−1)i+2(i+1)2\sum_{i=1}^5 \frac{(-1)^{i+1}}{i^2} = \sum_{i=0}^4 \frac{(-1)^{i+2}}{(i+1)^2}

  7. Theorem: ∑i=1n(cf(xi)+dg(xi))=c∑i=1nf(xi)+d∑i=1ng(xi)\sum_{i = 1}^n \left(cf(x_i) + dg(x_i)\right) = c\sum_{i=1}^n f(x_i) + d\sum_{i=1}^n g(x_i) for all constants c,dc,d.

1.1 Estimating the area of regions bounded by a curve y=f(x)y= f(x) and the xx-axis

Let f(x)=x2f(x)= x^2 on the interval [1,10][1,10]. For the area under the curve, we subdivide the interval into nn small intervals of size Δx\Delta x and make rectangles of heights f(xi)f(x_i). Then an approximate area under the curve is given by the sum of the area of these approximating rectangles.

That is, Δx=(10−1)/n=9/n\Delta x= (10-1)/n = 9/n and the sample points are xi=1+iΔx=1+9i/nx_i = 1 + i\Delta x = 1 + 9i/n, so Approximate area =∑i=1nAi=∑i=1nf(xi)⋅Δx=∑i=1n(1+9i/n)2⋅9/n=9n∑i=1n(1+18in+81i2n2)=9n(n+18n∑i=1ni+81n2∑i=1ni2)=9n(n+18nn(n+1)2+81n2n(n+1)(2n+1)6)=9n(n+9(n+1)+27(n+1)(2n+1)2n)=9+81+81n+243(2n2+3n+1)2n2=90+81n+243+243(3)2n+2432n2\begin{align*} \text{Approximate area }&= \sum_{i=1}^n A_i = \sum_{i=1}^n f(x_i)\cdot\Delta x \\ &= \sum_{i=1}^n (1+9i/n)^2 \cdot 9/n\\ &=\frac{9}{n}\sum_{i=1}^n \left( 1+ \frac{18i}{n} + \frac{81i^2}{n^2}\right)\\ &= \frac{9}{n}\left(n + \frac{18}{n}\sum_{i=1}^n i + \frac{81}{n^2}\sum_{i=1}^ni^2\right)\\ &=\frac{9}{n}\left(n + \frac{18}{n}\frac{n(n+1)}{2} + \frac{81}{n^2}\frac{n(n+1)(2n+1)}{6}\right)\\ &=\frac{9}{n}\left(n + 9(n+1) + \frac{27(n+1)(2n+1)}{2n}\right)\\ &= 9 + 81 + \frac{81}{n} + \frac{243(2n^2 + 3n+ 1)}{2n^2}\\ &= 90 + \frac{81}{n} + 243 + \frac{243(3)}{2n} + \frac{243}{2n^2} \end{align*} The actual area is given by allowing the number of rectangles to become infinite (hence, arbitrarily small), thus letting nn tend to infinity. That is, the actual area is found as limn→∞(90+81n+243+243(3)2n+2432n2)=90+243=333.\lim_{n\to \infty} \left(90 + \frac{81}{n} + 243 + \frac{243(3)}{2n} + \frac{243}{2n^2}\right) = 90+243 = 333. Note: the choice of sample points were the right hand sides of the rectangles, which gave us an over-estimate. One could also have chosen the left-hand sides of the rectangles and obtained an under-estimate and both would have the same limit.

2 The Definite Integral

Let f(x)f(x) be a continuous function on [a,b][a,b] and let Δx=b−an\Delta x = \frac{b-a}{n} for a known integer n>0n>0. Let xi*x_i^* be a sample point in each Δx\Delta x interval , then the expression ∑i=1nf(xi*)Δx\sum_{i=1}^n f(x_i^*)\Delta x is called a Riemann sumover [a,b][a,b]. The number obtained by lim⁡n→∞∑i=1nf(xi*)Δx\lim_{n\to \infty} \sum_{i=1}^n f(x_i^*)\Delta x is called a definite integral of f(x)f(x) over [a,b][a, b]. The definite integral is then denoted by ∫abf(x)dx=limn→∞∑i=1nf(xi*)Δx\begin{equation} \label{definiteintegral}\boxed{\int_a^bf(x)dx = \lim_{n\to \infty} \sum_{i=1}^n f(x_i^*)\Delta x} \end{equation}(1) where

  • f(x)f(x) is the integrand

  • ∫\int is the integral sign

  • a,ba,b are the limits of integration

and this process is called integration. If f(x)f(x) is a function on [a,b][a,b] such that ∫abf(x)dx\int_a^bf(x)dx exists, we say that f(x)f(x) is integrable on [a,b][a, b].

Theorem 1. If f(x)f(x) is continuous on [a,b][a, b], then it is integrable on [a,b][a, b] (i.e. ∫abf(x)dx\int_a^b f(x)dx exists).

Definition 1. If f(x)f(x) is continuous and non-negative on [a,b][a, b], then we define the area of the region bounded by f(x)f(x) and the xx-axis over [a,b][a, b] as being the positive number obtained by ∫abf(x)dx\int_a^bf(x)dx. In the case that f(x)f(x) is negative, we take the absolute value and if f(x)≥0f(x)\geq 0 on [a,c][a,c] then f(x)≤0f(x)\leq 0 on [c,b][c,b] where a<c<ba<c<b, then the area is ∫acf(x)dx+(−∫cbf(x)dx)\int_a^cf(x)dx + \left(-\int_c^b f(x)dx\right).

Example 1. Using Riemann sums to find a formula for ∫abxdx\int_a^b x dx (where 0<a<b0<a<b).

∫abxdx=limn→∞∑i=1n(a+(b−a)in)⋅b−an=limn→∞∑i=1n(aΔx+iΔx2)=limn→∞(aΔx∑i=1n1+Δx2∑i=1ni)=limn→∞(aΔxn+Δx2n(n+1)2)=limn→∞(a(b−a)+(b−a)2n2⋅n2+n2)=a(b−a)+limn→∞((b−a)22+(b−a)22n)=a(b−a)+(b−a)22=b2−a22\begin{align*} \int_a^b xdx &= \lim_{n\to \infty}\sum_{i=1}^n \left(a + \frac{(b-a)i}{n}\right)\cdot \frac{b-a}{n}\\ &= \lim_{n\to \infty}\sum_{i=1}^n \left( a\Delta x + i \Delta x^2 \right)\\ &= \lim_{n\to \infty}\left(a\Delta x \sum_{i=1}^n 1 + \Delta x^2 \sum_{i=1}^n i\right)\\ &= \lim_{n\to \infty}\left(a\Delta x n + \Delta x^2 \frac{n(n+1)}{2}\right)\\ &= \lim_{n\to \infty}\left(a(b-a) + \frac{(b-a)^2}{n^2}\cdot\frac{n^2 + n}{2}\right)\\ &= a(b-a) + \lim_{n\to \infty}\left( \frac{(b-a)^2}{2}+ \frac{(b-a)^2}{2n}\right)\\ &= a(b-a) + \frac{(b-a)^2}{2}\\ &= \frac{b^2 - a^2}{2} \end{align*}

2.1 Properties of the definite integral

We provide the following list of properties without proof. Note that, geometrically, these results should be intuitive.

  1. ∫abf(x)dx=−∫baf(x)dx\int_a^bf(x)dx = - \int_b^af(x)dx

  2. ∫abf(x)dx=∫acf(x)dx+∫cbf(x)dx\int_a^b f(x)dx = \int_a^c f(x)dx + \int_c^b f(x)dx

  3. ∫ab(f(x)±g(x))dx=∫abf(x)dx±∫abg(x)dx\int_a^b (f(x)\pm g(x)) dx = \int_a^b f(x)dx \pm \int_a^b g(x) dx

  4. ∫abλf(x)dx=λ∫abf(x)dx\int_a^b \lambda f(x)dx = \lambda \int_a^b f(x)dx

  5. if f(x)≥0f(x)\geq 0 on [a,b][a,b], then ∫abf(x)dx≥0\int_a^b f(x)dx\geq 0

  6. if f(x)f(x) is odd (i.e. f(−x)=−f(x)f(-x) = - f(x)), then ∫−aaf(x)dx=0\int_{-a}^a f(x)dx = 0

  7. if f(x)f(x) is even (i.e. f(−x)=f(x)f(-x) = f(x)), then ∫−aaf(x)dx=2∫0af(x)dx\int_{-a}^a f(x)dx = 2\int_0^af(x)dx

  8. If f(x)≥g(x)f(x)\geq g(x) on [a,b][a,b] then ∫abf(x)dx≥∫abg(x)dx,\int_a^bf(x)dx \geq \int_a^b g(x) dx,

  9. If m≤f(x)≤Mm\leq f(x) \leq M for all xx on [a,b][a,b], then m(b−a)≤∫abf(x)dx≤M(b−a)m(b-a)\leq \int_a^bf(x)dx\leq M(b-a)

  10. ∫aaf(x)dx=0\int_a^af(x) dx = 0

Example 2. Show that ∫231x2+1dx\int_2^3\frac{1}{x^2 + 1} dx is in the interval [1/10,1/5][1/10, 1/5].

Note, for x∈[2,3]x\in [2,3] that x2+1∈[5,10]x^2 +1 \in [5,10] or equivalently that 5≤x2+1≤105\leq x^2 + 1\leq 10 for all x∈[2,3]x\in [2, 3]. Hence, also, m:=1/10≤1x2+1≤1/5=:Mm:= 1/10\leq \frac{1}{x^2+1} \leq 1/5=:M and our properties guarantee, that 110=3−210≤∫231x2+1dx≤15.\frac{1}{10} = \frac{3-2}{10} \leq \int_2^3 \frac{1}{x^2+1}dx \leq \frac{1}{5}.

Example 3. Evaluate; ∫−132|x|dx=2[∫−10−xdx+∫03xdx]=2(12+92)\int_{-1}^3 2|x|dx = 2\left[\int_{-1}^0 -x dx + \int_0^3 xdx\right] = 2(\tfrac{1}{2} +\tfrac{9}{2})

2.2 Average Value of a Function

Suppose f(x)f(x) is integrable on [a,b][a,b] with a<ba<b. The average value of ff on [a,b][a,b] is defined as A(f)[a,b]=1b−a∫abf(x)dx\begin{equation} \label{averagevalue}\boxed{A(f)_{[a,b]} = \frac{1}{b-a}\int_a^b f(x)dx} \end{equation}(2)

Example 4. Find the average value of f(x)=100−3x2f(x)=100-3x^2 on [1,5][1, 5].

A(f)[1,5]=15−1∫15(100−3x2)dx=14(276)=69A(f)_{[1,5]} = \frac{1}{5-1} \int_1^5 (100-3x^2)dx = \frac{1}{4}(276) = 69

Theorem 2 (Average-value Theorem). Suppose ff is continuous on [a,b][a,b], with a<ba<b. Then there exists an x*∈[a,b]x^*\in [a,b] such that f(x*)=A(f)[a,b]f(x^*) = A(f)_{[a,b]}. That is, a continuous function actually achieves its averages value somewhere within the interval [a,b][a,b].

Proof. Since f(x)f(x) is continuous there exist a minimum and maximum at some c,d∈[a,b]c,d\in [a,b] respectively . Then, certainly f(c)≤f(x)≤f(d)f(c)\leq f(x)\leq f(d) for all x∈[a,b]x\in [a,b]. Now, from property 9, we have f(c)(b−a)≤∫abf(x)dx≤f(d)(b−a)f(c)(b-a)\leq \int_a^bf(x)dx\leq f(d)(b-a) or equivalently (dividing by (b−a)(b-a)) f(c)≤1b−a∫abf(x)dx≤f(d).f(c)\leq \frac{1}{b-a}\int_a^bf(x)dx\leq f(d). Now, by the intermediate value theorem, there exists x*∈[c,d]x^*\in[c,d] such that f(x*)=1b−a∫abf(x)dxf(x^*) = \frac{1}{b-a}\int_a^bf(x)dx. ◻

2.3 Fundamental Theorem of Calculus - Part I

Theorem 3 (FTC I). Suppose f(x)f(x) is continuous on [a,b][a, b]. Let F(x)F(x) be a function on [a,b][a, b] defined as F(x)=∫axf(t)dtF(x) = \int_a^x f(t) dt. Then F′(x)=f(x)F'(x) = f(x).

Proof. Let x∈[a,b]x\in[a,b] and proceed computing the derivative by first principles. F′(x)=limh→0F(x+h)−F(x)h=limh→01h[∫ax+hf(t)dt−∫axf(t)dt]=limh→01h[∫axf(t)dt+∫xx+hf(t)dt−∫axf(t)dt]=limh→01h∫xx+hf(t)dt\begin{align*} F'(x) &= \lim_{h\to 0} \frac{F(x+h) - F(x)}{h}\\ &= \lim_{h\to 0} \frac{1}{h}\left[ \int_a^{x+h}f(t) dt - \int_a^x f(t) dt\right]\\ &= \lim_{h\to 0} \frac{1}{h}\left[ \int_a^{x}f(t) dt + \int_x^{x+h}f(t)dt - \int_a^x f(t) dt\right]\\ &= \lim_{h\to 0} \frac{1}{h} \int_x^{x+h}f(t) dt \end{align*} By the average value theorem there is an x*∈[x,x+h]x^*\in [x,x+h] so that f(x*)=1h∫xx+hf(t)dtf(x^*)= \frac{1}{h} \int_x^{x+h}f(t) dt so then F′(x)=limh→01h∫xx+hf(t)dt=limh→0f(x*)=limx*→xf(x*)=f(limx*→x)=f(x)\begin{align*} F'(x) = \lim_{h\to 0} \frac{1}{h} \int_x^{x+h}f(t) dt = \lim_{h\to 0} f(x^*) = \lim_{x^*\to x} f(x^*) = f\left(\lim_{x^*\to x} \right) = f(x) \end{align*} as required. ◻

Example 5.

  1. ddt∫0tx2+1dt=t2+1\frac{d}{dt}\int_0^t\sqrt{x^2 + 1} dt = \sqrt{t^2+ 1}

  2. ddt∫t−3sin⁡2(x)dx=−ddt∫−3tsin⁡2(x)dx=−sin⁡2(t)\frac{d}{dt}\int_t^{-3} \sin^2(x)dx = - \frac{d}{dt}\int_{-3}^t \sin^2(x)dx = -\sin^2(t)

  3. ddt∫0t2cos⁡(x2)dx=ddt∫0u(t)cos⁡(x2)dx=ddu∫0ucos⁡(x2)dx⋅dudt=cos⁡(u2)⋅2t=2tcos⁡(t4)\begin{align*} \frac{d}{dt}\int_0^{t^2} \cos(x^2)dx &= \frac{d}{dt}\int_0^{u(t)}\cos(x^2) dx \\ &= \frac{d}{du}\int_0^u\cos(x^2) dx \cdot\frac{du}{dt}\\ &= \cos(u^2) \cdot 2t\\ & =2t \cos(t^4) \end{align*}

  4. ddt∫−2tt11+x2dx=ddt(−∫0−2t11+x2dx+∫0t11+x2dx)=−−21+4t2+11+t2\frac{d}{dt}\int_{-2t}^t \frac{1}{1+ x^2} dx = \frac{d}{dt}\left(-\int_0^{-2t}\frac{1}{1+x^2}dx + \int_0^t \frac{1}{1+x^2}dx\right) = - \frac{-2}{1+4t^2} + \frac{1}{1+t^2}

Lemma 1. If ff and gg are two functions whose derivative is FF, then f(x)=g(x)+cf(x) = g(x) + c

Proof. Given that f′(x)=F(x)=g′(x)f'(x) = F(x) = g'(x), then ddx(f(x)−g(x))=F(x)−F(x)=0⇒f(x)−g(x)=c\frac{d}{dx}(f(x) - g(x)) = F(x) - F(x) = 0\Rightarrow f(x) - g(x) = c since the derivative of a constant is 0. ◻

2.4 Fundamental Theorem of Calculus II

Definition 2. A function FF is called an antiderivative of ff on an interval II if F′(x)=f(x)F'(x) = f(x) for all x∈Ix\in I.

Theorem 4 (FTC II). Suppose f(x)f(x) is continuous on [a,b][a, b] and let F(x)F(x) be any anti-derivative of f(x)f(x) (i.e. F′(x)=f(x)F'(x) = f(x)). Then ∫abf(x)dx=F(b)−F(a)\begin{equation} \label{FTC2}\boxed{ \int_a^bf(x)dx = F(b) - F(a)} \end{equation}(3)

Proof. Given that f(x)f(x) is continuous on [a,b][a,b] and F′(x)=f(x)F'(x) = f(x), let G(x)=∫axf(t)dtG(x)=\int_a^xf(t) dt so that G′(x)=f(x)G'(x) = f(x) too. By the previous lemma, then, there is some constant cc such that G(x)=F(x)+cG(x) = F(x) + c. Now, ∫abf(t)dt=G(b)=G(b)−0=G(b)−G(a)=(F(b)+c)−(F(a)+c)=F(b)−F(a)\begin{align*} \int_a^bf(t)dt = G(b) = G(b)-0 = G(b) - G(a) = (F(b) + c) - (F(a) + c) = F(b) - F(a) \end{align*} ◻

This theorem says that knowing any anti-derivative f(x)f(x) allows us to compute any definite integral.

Example 6. Now we are able to compute a few more definite integrals like ∫23exdx=ex|23=e3−e2\int_2^3 e^xdx = e^x|_2^3 = e^3 - e^2 and ∫−7500sin⁡xdx=−cos⁡(500)−(−cos⁡(−7))\int_{-7}^{500} \sin xdx = - \cos(500) - (-\cos(-7))

Notation: If F(x)F(x) is an antiderivative of f(x)f(x) denote by ∫f(x)dx\int f(x)dx the family of antiderivatives F(x)+CF(x)+C and call this the indefinite integral of f(x)f(x).

2.5 A few antiderivatives

  • ∫kdx=kx+C\int kdx = kx+C

  • ∫xndx=xn+1n+1+C\int x^ndx = \frac{x^{n+1}}{n+1} + C

  • ∫exdx=ex+C\int e^x dx = e^x + C

  • ∫1xdx=ln⁡|x|+C\int \frac{1}{x}dx = \ln|x| + C

  • ∫sin⁡xdx=−cos⁡x+C\int \sin x dx = -\cos x + C

  • ∫cos⁡xdx=sin⁡x+C\int\cos xdx = \sin x + C

  • ∫sec⁡2dx=tan⁡x+C\int\sec^2 dx = \tan x + C

  • ∫sec⁡xtan⁡xdx=sec⁡x+C\int\sec x \tan x dx = \sec x + C

Example 7. Find the reigon bounded by cos⁡x\cos x and the xx-axis over the interval [0,π][0, \pi].

Note: ∫0πcos⁡xdx\int_0^\pi \cos xdx won’t work since the function is negative on the second half of this interval. Must use, A=A1+A2=∫0π/2cos⁡xdx+(−∫π/2πcosxdx)=sin⁡x|0π/2−sin⁡x|π/2π=(1−0)−(0−1)=2A = A_1 + A_2 = \int_0^{\pi/2} \cos xdx + \left(-\int_{\pi/2}^\pi\cos x dx \right) = \sin x|_0^{\pi/2} - \sin x|_{\pi/2}^\pi = (1-0) - (0-1) = 2

Example 8. ∫−111x2\int_{-1}^1\frac{1}{x^2} does not exist since 1x2\frac{1}{x^2} is not continuous at 00 and (3) does not apply.

Definition 3. Let y=f(x)y = f(x) be continuous, we define the differential of yy, denoted by dydy, as being dy=f′(x)Δxdy = f'(x) \Delta x where Δx=x1−x\Delta x = x_1 - x and x1>xx_1 >x.

Observation: if y=xy=x, then dy=dx=dxdx⋅Δx=Δxdy = dx = \frac{dx}{dx}\cdot \Delta x = \Delta x so Δx=dx\Delta x = dx and so, if y=f(x)y = f(x) then dy=f′(x)dxdy = f'(x) dx.

3 Techniques of integration

3.1 Integration by Substitution

Theorem 5 (The substitution rule). Let u=g(x)u = g(x) be differentiable and having as its image, the interval II. Suppose f(x)f(x) is continuous on the interval II. Then, ∫f(g(x))⋅g′(x)dx=∫f(u)du\begin{equation} \label{substitution}\boxed{ \int f(g(x)) \cdot g'(x) dx = \int f(u) du} \end{equation}(4)

Proof. Given that u=g(x)u = g(x), we are required to show that the general antiderivative of f(g(x))⋅g′(x)f(g(x)) \cdot g'(x) is the same as the general antiderivative (AD) of f(u)f(u).

Suppose F(u)F(u) is an AD of f(u)f(u), then ∫f(u)du=F(u)+C=F(g(x))+C\int f(u) du = F(u) + C = F(g(x)) + C.

Now we claim that ∫f(g(x))g′(x)=F(g(x))+C\int f(g(x)) g'(x) = F(g(x) ) + C. Indeed, it remains to show that ddx(F(g(x))+C=f(g(x))g′(x)\frac{d}{dx} (F(g(x)) + C = f(g(x))g'(x) which is true by the chain rule so the theorem holds. ◻

Remark 1. What the substitution rule is saying is that ∫f(g(x))⏟f(u)g′(x)dx⏟du\int \underbrace{f(g(x))}_{f(u)}\underbrace{g'(x)dx}_{du} and thats it!

Example 9. letting u=x3+9u = x^3+9 so that du=3x2dxdu = 3x^2 dx which is equivalent to x2dx=13dux^2dx = \frac{1}{3}du, we find ∫03x2x3+9dx=∫x=0x=313udu=13(23u2/3)|x=0x=3=29(x3+9)2/3|03=42\begin{align*} \int_0^3 x^2\sqrt{x^3+9}dx &= \int_{x=0}^{x=3}\frac{1}{3}\sqrt{u}du\\ & = \frac{1}{3}\left(\frac{2}{3}u^{2/3}\right)|_{x=0}^{x=3}\\ &=\frac{2}{9}(x^3+9)^{2/3}|_0^3 = 42 \end{align*}

Example 10. Here will will use u=sin⁡xu = \sin x. ∫sin⁡3xcos⁡xdx=∫u3=u44+C=sin⁡4x4+C\int\sin^3 x\cos xdx = \int u^3 = \frac{u^4}{4} + C = \frac{\sin^4 x}{4} + C

3.2 Integration by Parts

Consider two functions u(x),v(x)u(x), v(x). The product rule says that ddx(u(x)⋅v(x))=u′(x)v(x)+u(x)v′(x).\frac{d}{dx}(u(x)\cdot v(x)) = u'(x) v(x) + u(x) v'(x). Integrating both sides of this equation now says that u(x)v(x)=∫[u(x)v(x)]′=∫u′(x)v(x)dx+∫u(x)v′(x)dx=∫v(x)du+∫u(x)dv.u(x)v(x) = \int \left[u(x)v(x)\right]' = \int u'(x)v(x)dx + \int u(x) v'(x)dx = \int v(x) du + \int u(x) dv. Rearranging, that is ∫u(x)dv=u(x)v(x)−∫v(x)du\int u(x) dv = u(x) v(x) - \int v(x) du or in more compact notation ∫udv=uv−∫vdu\begin{equation} \label{IBP}\boxed{\int u dv = uv -\int vdu} \end{equation}(5)

Recall that ddxarcsin⁡x=11−x2⇒∫dx1−x2=arcsin⁡x+C\frac{d}{dx}\arcsin x = \frac{1}{\sqrt{1-x^2}}\Rightarrow \int\frac{dx}{\sqrt{1-x^2}} = \arcsin x + C ddxarccos⁡x=−11−x2⇒−∫dx1−x2=arccos⁡x+C\frac{d}{dx}\arccos x = \frac{-1}{\sqrt{1-x^2}}\Rightarrow- \int\frac{dx}{\sqrt{1-x^2}} = \arccos x + C ddxarctan⁡x=11+x2⇒∫dx1+x2=arctan⁡x+C\frac{d}{dx}\arctan x = \frac{1}{1+x^2}\Rightarrow \int\frac{dx}{1+x^2} = \arctan x + C

Example 11. Now for a long list of examples with solutions!

  1. ∫arcsin⁡xdx=xarcsin⁡x+1−x2+C.\int\arcsin xdx = x\arcsin x + \sqrt{1-x^2} + C. Solution: With u=arcsin⁡x,dv=dxu = \arcsin x ,dv = dx, so that du=11−x2,v=xdu = \frac{1}{\sqrt{1-x^2}}, v = x (using integration by parts - IBP) we find ∫arcsin⁡xdx=xarcsin⁡x−∫x1−x2dx.\begin{align*} \int \arcsin x dx = x\arcsin x - \int \frac{x}{\sqrt{1-x^2}} dx. \end{align*} Now, the substitution y=1−x2y = 1-x^2 so that dy=−2xdxdy = -2xdx or xdx=−dy2xdx = -\frac{dy}{2} reveals the above as xarcsin⁡x−12∫y−1/2dy=xarcsin⁡x+122y+C=xarcsin⁡x+1−x2+C.x\arcsin x- \frac{1}{2}\int y^{-1/2}dy = x\arcsin x + \frac{1}{2} 2\sqrt{y} + C = x\arcsin x + \sqrt{1-x^2} + C.

  2. ∫x2e−xdx=−e−x(x2+2x+2)+C\int x^2 e^{-x}dx = -e^{-x}(x^2 + 2x + 2) + C Solution: This will require two iterations of IBP. First we will have u=x2u = x^2 and dv=e−xdxdv = e^{-x}dx so that du=2xdxdu = 2xdx and v=−e−xv = -e^{-x}. The first iteration becomes ∫x2e−xdx=−x2e−x−∫(−2x)e−xdx=−x2e−x+2∫xe−xdx.\int x^2 e^{-x}dx = -x^2 e^{-x} - \int (-2x)e^{-x}dx = -x^2 e^{-x} +2 \int xe^{-x}dx. For the second term we use u=x,dv=e−xdxu = x, dv = e^{-x}dx so that du=dx,v=−e−xdu = dx, v = -e^{-x} and the above becomes −x2e−x+2[−xe−x+∫e−xdx]=−x2e−x−2xe−x−2e−x+C-x^2 e^{-x} +2\left[-xe^{-x} + \int e^{-x}dx \right] = -x^2 e^{-x}-2xe^{-x} - 2e^{-x}+C as required.

  3. ∫e2xsin⁡(3x)dx=132e2x(2sin(3x)−32cos(3x))+C\int e^{2x}\sin(3x)dx = \frac{13}{2}e^{2x}\left(2\sin(3x) - \frac{3}{2}\cos(3x)\right) + C Solution: This will also require two iterations of IBP, but has a slightly different solution.

    Let u=sin⁡(3x),dv=e2xdxu= \sin(3x), dv = e^{2x}dx so du=3cos⁡(3x)dx,v=12e2xdu = 3\cos(3x)dx, v = \frac{1}{2}e^{2x},

    ∫e2xsin⁡(3x)dx=12sin⁡(3x)e2x−32∫e2xcos⁡(3x)dx\int e^{2x}\sin(3x)dx = \tfrac{1}{2}\sin(3x)e^{2x} - \tfrac{3}{2}\int e^{2x}\cos(3x)dx Now for the second term, use u=cos⁡(3x),dv=e2xdxu = \cos(3x) , dv = e^{2x}dx so that du=−3sin⁡(3x)dx,v=12e2xdu = -3\sin(3x) dx, v = \frac{1}{2}e^{2x} and then the integral from the second term above becomes ∫e2xcos⁡(3x)dx=12cos⁡(3x)e2x+32∫e2xsin⁡(3x)dx.\int e^{2x}\cos(3x)dx = \tfrac{1}{2}\cos(3x)e^{2x} +\tfrac{3}{2}\int e^{2x}\sin(3x)dx. Notice that the original integral y=∫e2xsin⁡(3x)dxy = \int e^{2x}\sin(3x)dx has reappeared. However, this doesn’t mean we have gone in a circle since other terms have come out. Putting these together reads y=12sin⁡(3x)e2x−32∫e2xcos⁡(3x)dx=12sin⁡(3x)e2x−32[12cos(3x)e2x+32∫e2xsin(3x)dx]=e2x2(sin(3x)−32cos(3x))−94y\begin{align*} y &= \tfrac{1}{2}\sin(3x)e^{2x} - \tfrac{3}{2}\int e^{2x}\cos(3x)dx \\ &= \tfrac{1}{2}\sin(3x)e^{2x} - \tfrac{3}{2}\left[\tfrac{1}{2}\cos(3x)e^{2x} +\tfrac{3}{2}\int e^{2x}\sin(3x)dx\right] \\ &= \tfrac{e^{2x}}{2}\left(\sin(3x) - \tfrac{3}{2}\cos(3x)\right) - \tfrac{9}{4}y \end{align*} or in other words, (1+94)y=e2x2(sin(3x)−32cos(3x))⇒y=213e2x(sin⁡(3x)−32cos⁡(3x))(1+\tfrac{9}{4}) y = \frac{e^{2x}}{2}\left(\sin(3x) - \tfrac{3}{2}\cos(3x)\right)\Rightarrow\boxed{ y = \tfrac{2}{13}e^{2x} (\sin(3x)- \tfrac{3}{2}\cos(3x))}

  4. ∫sec⁡3xdx=12sec⁡xtan⁡x+12ln⁡|sec⁡x+tan⁡x|+C\int \sec^3xdx = \frac{1}{2}\sec x\tan x + \frac{1}{2}\ln|\sec x + \tan x|+ C Solution: Here again we will find a similar solution to the previous problem. Let II denote the value of interest, ∫sec⁡3xdx\int \sec^3 x dx, (for later when we need to rearrange). For IBP, use u=sec⁡x,dv=sec2xdxu = \sec x, dv = sec^2 x dx so that du=sec⁡xtan⁡xdx,v=tan⁡xdu = \sec x\tan x dx, v = \tan x. Now I=sec⁡xtan⁡x−∫sec⁡xtan⁡2xdx=sec⁡xtan⁡x−∫sec⁡x(sec⁡2x−1)dx=sec⁡xtan⁡x−∫sec⁡3xxdx+∫sec⁡xdx=sec⁡xtan⁡x−I+ln⁡|sec⁡xtan⁡x|+C\begin{align*} I &= \sec x\tan x - \int\sec x\tan^2 xdx \\ &=\sec x\tan x - \int\sec x(\sec^2 x - 1) dx\\ & = \sec x\tan x - \int\sec^3 x xdx + \int\sec xdx = \sec x\tan x - I + \ln |\sec x\tan x| + C \end{align*} So, rearranging, 2I=sec⁡xtan⁡x+ln⁡|sec⁡xtan⁡x|+C⇒I=12(secxtanx+ln|secxtanx|)+C2I = \sec x\tan x + \ln |\sec x\tan x| + C\Rightarrow \boxed{I =\frac{1}{2}\left( \sec x\tan x + \ln |\sec x\tan x| \right)+ C}

3.3 Trigonometric Integrals

Recall and remember the following trigonometric identities: sin⁡(A±B)=sin⁡Acos⁡B±cos⁡Asin⁡B\sin(A\pm B ) = \sin A \cos B \pm \cos A \sin B cos⁡(A±B)=cos⁡Acos⁡B∓sin⁡Asin⁡B\cos (A\pm B) = \cos A \cos B \mp \sin A \sin B cos⁡2x=12(1+cos2x),sin⁡2x=12(1−cos2x), and sin⁡2x+cos⁡2x=1\cos ^2 x = \frac{1}{2}\left(1+ \cos 2x\right), \quad\sin^2 x = \frac{1}{2} \left(1 - \cos 2x\right),\text{ and } \sin^2 x + \cos^2 x = 1

Now, we will Evaluate: ∫sin⁡mxcos⁡nxdx\boxed{\text{Evaluate: } \int\sin^m x\cos ^n xdx} by considering three different cases.

Solution:

  • when nn is odd;

    Write n=2k+1n = 2k+1 , then by the substitution u=sin⁡xu = \sin x ∫sin⁡mxcos⁡2k+1xdx=∫sin⁡mx(cos⁡2x)kcos⁡xdx=∫sin⁡mx(1−sin⁡2x)kcos⁡xdx=∫um(1−u2)kdu\begin{align*} \int \sin^m x\cos^{2k+1}x dx & = \int \sin^m x (\cos^2 x)^k \cos xdx \\ &= \int \sin^m x (1- \sin^2 x)^k \cos xdx\\ &= \int u^m(1-u^2)^k du \end{align*} and this is easy to evaluate (begin a polynomial).

  • when mm is odd;

    Write m=2k+1m = 2k+1 and the substitution u=cos⁡xu = \cos x ∫(sin⁡2x)kcos⁡nxsin⁡xdx=−∫(1−u2)kundu\begin{align*} \int (\sin^2 x)^k \cos^n x \sin xdx& =- \int (1-u^2)^ku^n du \end{align*}

  • when both mm and nn are even;

    The identity cos⁡2x=12(1+cos⁡(2x)) or sin⁡2x=12(1−cos⁡(2x))\cos^2 x= \tfrac{1}{2}( 1+ \cos(2x)) \text{ or } \sin^2 x = \tfrac{1}{2}( 1- \cos(2x)) followed by sin⁡xsin⁡y=12(sin⁡(x+y)+sin⁡(x−y)) or cos⁡xcos⁡y=12(cos⁡(x+y)+cos⁡(x−y))\sin x \sin y = \tfrac{1}{2} (\sin(x+ y) + \sin(x-y)) \text{ or } \cos x\cos y = \tfrac{1}{2}(\cos (x+y) + \cos(x - y)) will bring one of the even powers down to either case (i) or case (ii).

and similarly,

Evaluate: ∫tan⁡mxsec⁡nxdx\boxed{\text{Evaluate: }\int\tan^m x \sec^n x dx}

  • If nn is even, say n=2kn=2k, then the substitution u=tan⁡xu = \tan x and du=sec⁡2xdxdu = \sec^2 xdx gives ∫tan⁡mx(sec⁡2x)kdx=∫tan⁡msec⁡2k−2xsec⁡2xdx=∫tan⁡m(sec⁡2x)k−1sec⁡2xdx=∫tan⁡m(1+tan⁡2x)k−1sec⁡2xdx=∫um(1+u2)k−1du\begin{align*} \int \tan^mx (\sec^2x)^kdx&= \int\tan^m \sec^{2k-2}x \sec^2 xdx \\ &= \int\tan^m (\sec^2x)^{k-1} \sec^2 xdx \\ &= \int\tan^m (1+\tan^2 x)^{k-1} \sec^2 xdx \\ &= \int u^m(1+u^2)^{k-1}du \end{align*}

  • If mm is odd, then we will substitute u=sec⁡xu = \sec x with du=sec⁡xtan⁡xdxdu = \sec x \tan xdx like so ∫tan⁡2k+1xsec⁡nxdx=∫(tan⁡2x)ksec⁡n−1xsec⁡xtan⁡xdx=∫(sec⁡2x−1)ksec⁡n−1xsec⁡xtan⁡xdx=∫(u2−1)kun−1du\begin{align*} \int \tan^{2k+1}x \sec ^n xdx&= \int (\tan^2x)^k \sec^{n-1}x \sec x\tan x dx\\ &= \int (\sec^2 x - 1)^k \sec^{n-1}x \sec x\tan x dx\\ &= \int(u^2 -1 )^k u^{n-1}du \end{align*}

In any other case, we won’t find a closed expression for the integral ∫tan⁡mxsec⁡nxdx\int \tan^mx \sec^n x dx.

Example 12. Now for a list of examples with solutions!

  1. ∫sin⁡3xcos⁡2xdx=∫(1−cos⁡2x)cos⁡2xsin⁡xdx,u=cos⁡x,du=−sin⁡xdx=−∫(1−u2)u2du=−∫(u2−u4)du=u55−u33+C=cos⁡5x5−cos⁡3x3+C\begin{align*} \int\sin^3x\cos^2xdx &=\int (1- \cos^2x)\cos^2x \sin xdx, \qquad u = \cos x, du = - \sin xdx\\ &= - \int (1-u^2)u^2du\\ &=- \int(u^2 - u^4)du\\ &= \frac{u^5}{5} - \frac{u^3}{3} + C\\ &= \frac{\cos^5x}{5} - \frac{\cos^3 x}{3} + C \end{align*}

  2. ∫cos⁡5xdx=∫(1−sin⁡2x)2cos⁡xdx,u=sin⁡x,du=cos⁡xdx=∫(1−u2)2du=∫(1−2u2+u4)du−u−2u33+u55+C=sin⁡x−2sin⁡3x3+sin⁡5x5+C\begin{align*} \int \cos^5 xdx &= \int(1-\sin^2 x)^2 \cos x dx, \qquad u = \sin x, du = \cos xdx\\ &= \int(1-u^2)^2du\\ &=\int (1 - 2u^2 + u^4)du\\ &- u - \frac{2u^3}{3} + \frac{u^5}{5} + C\\ &= \sin x - \frac{2\sin^3 x}{3} + \frac{\sin^5 x}{5} + C \end{align*}

  3. ∫sin⁡2xcos⁡2xdx=∫(sin⁡xcos⁡x)2dx=∫(12sin(2x))2dx=14∫sin⁡2(2x)dx=14∫12(1−cos⁡(4x))dx=18∫(1−cos⁡(4x))dx=18x+18sin⁡(4x)4+C\begin{align*} \int \sin^2 x \cos^2 x dx & = \int(\sin x \cos x )^2 dx \\ &= \int \left(\tfrac{1}{2}\sin(2x)\right)^2dx\\ &= \tfrac{1}{4}\int \sin^2 (2x) dx\\ &= \tfrac{1}{4}\int \tfrac{1}{2}(1- \cos (4x)) dx\\ &= \tfrac{1}{8}\int (1-\cos (4x)) dx\\ &= \tfrac{1}{8}x + \tfrac{1}{8}\frac{\sin(4x)} {4} + C \end{align*}

  4. ∫tan⁡3xsec⁡xdx=∫(sec⁡2x−1)sec⁡2xsec⁡xtan⁡xdx,u=sec⁡x,du=sec⁡xtan⁡xdx=∫(u2−1)u2du=u55−u33+C\begin{align*} \int\tan^3 x\sec xdx & =\int(\sec^2 x - 1) \sec^2x \sec x\tan x dx, \qquad u = \sec x, du = \sec x\tan x dx\\ &= \int(u^2- 1)u^2du\\ &= \frac{u^5 }{5}- \frac{u^3}{3} + C \end{align*}

  5. ∫tan⁡4xsec⁡4xdx=∫tan⁡4x(tan⁡2x+1)sec⁡2xdx,u=tan⁡x,du=sec⁡2x=∫u4(u2+1)du=u77+u55+C\begin{align*} \int \tan^4x\sec^4xdx &= \int\tan^4 x(\tan^2x + 1) \sec^2xdx, \qquad u = \tan x, du = \sec^2 x\\ &= \int u^4(u^2 + 1)du\\ &= \frac{u^7}{7} + \frac{u^5}{5} + C \end{align*}

3.4 Trigonometric Substitution

This method will apply to integrands containing a2+x2,a2−x2a^2 + x^2, a^2- x^2 or x2−a2x^2 - a^2.

So, if

Integrand has substitute apply identity
a2−x2a^2 - x^2 x=asin⁡x,−π/2≤x≤π/2x = a\sin x, -\pi/2 \leq x \leq \pi/2 1−sin⁡2θ=cos⁡2xθ1- \sin^2 \theta = \cos ^2 x\theta
or cos⁡2θ=1/2(1+cos⁡2θ)\cos^2 \theta = 1/2(1 + \cos 2\theta)
x2−a2x^2- a^2 x=asec⁡x,−π/2≤x≤π/2x = a\sec x, -\pi/2 \leq x \leq \pi/2 sec⁡2θ−1=tan⁡2xθ\sec^2 \theta -1 = \tan^2 x\theta
or π≤x≤3π/2\pi \leq x \leq 3\pi/2
a2+x2a^2 + x^2 x=atan⁡x,−π/2≤x≤π/2x = a\tan x, -\pi/2 \leq x \leq \pi/2 1+tan⁡2θ=sec⁡2xθ1+ \tan^2 \theta = \sec^2 x\theta

Example 13. These ideas will be best demonstrated through a list of examples

  1. Letting x=sin⁡θx = \sin \theta so that on the interval −π/2≤θ≤π/2-\pi/2 \leq \theta \leq \pi/2 we have θ=arcsin⁡x\theta = \arcsin x and dx=cos⁡θdθdx = \cos \theta d\theta, then ∫x31−x2dx=∫sin⁡3θ1−sin⁡2θcos⁡θdθ=∫sin⁡3θ|cos⁡θ|cos⁡θdθ=∫sin⁡3θdθ=∫(1−cos⁡2θ)sin⁡θdθ,let u=cos⁡θ,du=−sin⁡θdθ=−∫(1−u2)du=−u+u33+C−cos⁡θ+cos⁡3θ3+C=−1−x2+1−x233+C\begin{align*} \int \frac{x^3}{\sqrt{1-x^2}} dx & = \int \frac{\sin^3\theta}{\sqrt{1-\sin^2 \theta}} \cos\theta d\theta\\ &= \int \frac{\sin^3 \theta } {|\cos \theta|} \cos \theta d\theta\\ & = \int \sin^3 \theta d\theta\\ &= \int (1-\cos^2\theta )\sin\theta d\theta, \qquad \text{let } u = \cos\theta, du = -\sin \theta d\theta\\ &= -\int(1-u^2)du \\ &= -u +\frac{u^3}{3}+C\\ &-\cos \theta + \frac{\cos^3\theta}{3}+C\\ &= -\sqrt{1-x^2} + \frac{\sqrt{1-x^2}^3}{3}+C \end{align*}

  2. The trigonometric substitution here is x=32tan⁡θx = \tfrac{3}{2}\tan \theta on −π/2≤θ≤π/2-\pi/2\leq \theta \leq \pi/2 so that θ=arctan⁡(2x/3)\theta = \arctan (2x/3) and dx=32sec⁡2θdθdx = \tfrac{3}{2}\sec^2 \theta d\theta, then ∫1(4x2+9)2dx=∫1(4(32tan⁡θ)2+9)2(32sec⁡2θ)dθ=181⋅32∫sec⁡2θsec⁡4θdθ=154∫1sec⁡2θdθ=154∫cos⁡2θdθ=154∫12(1+cos⁡(2θ))dθ=1108∫(1+cos⁡(2θ))dθ=1108(θ+12sin⁡(2θ))+C=1108(arctan⁡x+122sin⁡θcos⁡θ)+C=1108(arctan⁡x+sin⁡θcos⁡θ)+C=1108(arctan⁡x+2x4x2+9⋅34x2+9)+C\begin{align*} \int \frac{1}{(4x^2+9)^2}dx&= \int\frac{1}{(4(\tfrac{3}{2}\tan\theta)^2 + 9)^2} (\tfrac{3}{2}\sec^2 \theta)d\theta\\ &= \tfrac{1}{81}\cdot\tfrac{3}{2}\int \frac{\sec^2\theta}{\sec^4\theta} d\theta\\ &= \tfrac{1}{54}\int \frac{1}{\sec^2 \theta}d\theta\\ &= \tfrac{1}{54}\int \cos^2\theta d\theta\\ &= \tfrac{1}{54}\int\tfrac{1}{2}(1+ \cos(2\theta)) d\theta\\ &= \tfrac{1}{108}\int(1+ \cos(2\theta)) d\theta\\ &= \tfrac{1}{108}(\theta + \tfrac{1}{2}\sin(2\theta)) + C\\ &=\tfrac{1}{108}(\arctan x + \tfrac{1}{2}2\sin\theta\cos \theta) + C\\ &=\tfrac{1}{108}(\arctan x +\sin\theta\cos \theta) + C\\ &=\tfrac{1}{108}(\arctan x +\tfrac{2x}{4x^2 + 9}\cdot\tfrac{3}{4x^2 + 9}) + C \end{align*} where the last line is found from the fact that tan⁡θ=2x3\tan\theta = \frac{2x}{3} so the hypotenuse is necessarily 4x2+94x^2 + 9 hence cos⁡θ=34x2+9\cos\theta = \tfrac{3}{4x^2 + 9} and sin⁡θ=2x4x2+9\sin\theta = \tfrac{2x}{4x^2 + 9}.

  3. Here we use x=sin⁡θx = \sin \theta on π/2≤θ≤π/2\pi/2\leq \theta \leq \pi/2 so that dx=cos⁡θdθdx = \cos \theta d\theta. Note that this is definite integral so we have to change the bounds of integration. That is, when x=1/2,θ=π/6x = 1/2, \theta= \pi/6 and when x=3/2,θ=π/3x = \sqrt{3}/2, \theta= \pi/3. ∫1/23/2x31−x2dx=∫π/6π/3sin⁡3θcos⁡θ1−sin⁡2θdθ=∫π/6π/3sin⁡3θdθ, let u=cos⁡θ=∫π/6π/3(1−cos⁡2θ)sin⁡θdθ, let u=cos⁡θ=−∫u=3/2u=1/2(1−u2)du=[−u+u33]3/21/2=(124−12)−(3324−32)=93−1124\begin{align*} \int_{1/2}^{\sqrt{3}/2}\frac{x^3}{\sqrt{1-x^2}}dx & = \int_{\pi/6}^{\pi/3} \frac{\sin^3\theta\cos\theta}{\sqrt{1-\sin^2 \theta}}d\theta\\ &= \int_{\pi/6}^{\pi/3}\sin^3\theta d\theta, \text{ let } u = \cos \theta\\ &= \int_{\pi/6}^{\pi/3}(1-\cos^2\theta)\sin\theta d\theta, \text{ let } u = \cos \theta\\ &=- \int_{u = \sqrt{3}/2}^{u = 1/2}(1-u^2)du\\ &= \left[-u + \frac{u^3}{3}\right]_{\sqrt{3}/2}^{1/2}\\ &= \left(\tfrac{1}{24} - \tfrac{1}{2} \right) - \left(\tfrac{3\sqrt{3}}{24} - \tfrac{\sqrt{3}}{2}\right)\\ &= \tfrac{9 \sqrt{3} - 11}{24} \end{align*}

  4. Here we will use x+1=2sin⁡θx+1 = 2\sin \theta for |θ|≤π/2|\theta|\leq \pi/2 so θ=arcsin⁡(x+12)\theta= \arcsin\left(\tfrac{x+1}{2}\right) and dx=2cos⁡θdθdx = 2\cos \theta d\theta. Now ∫x3−2x−x2dx=∫x4−(x+1)2dx=∫(2sin⁡θ−1)2cos⁡θ4(1−sin⁡2θ)dθ=∫2sin⁡θ−1)cos⁡θcos⁡θdθ=2∫sin⁡θdθ−∫dθ=−2cos⁡θ−θ+C=−24−(x+1)2−arcsin⁡(x+12)+C\begin{align*} \int\frac{x}{\sqrt{3 - 2x - x^2}}dx& = \int \frac{x}{4- (x+1)^2}dx\\ &= \int \frac{(2\sin \theta-1)2\cos\theta}{\sqrt{4(1-\sin^2\theta)}}d\theta\\ &= \int \frac{2\sin \theta- 1) \cos\theta}{\cos\theta}d\theta\\ &= 2\int\sin \theta d\theta- \int d\theta\\ &= - 2\cos\theta- \theta+ C\\ &=- 2\sqrt{4 - (x+1)^2}- \arcsin\left(\tfrac{x+1}{2}\right)+ C \end{align*}

3.5 Integration with Partial Fractions

This method is used to solve a rational integrand (i.e. of the form p(x)q(x)\frac{p(x) }{q(x)} for polynomials pp and qq).

Case 1: deg⁡p≥deg⁡q\deg p \geq \deg q, use long division.

Case 2: deg⁡p<deg⁡q\deg p < \deg q, factor the denominator and split up with partial fractions.

Example 14. As usual, this is best demonstrated by example.

  1. ∫x3+x2+x−1x2+2x+2dx=∫(x−1)dx+∫x+1x2+2x+2dx,(long division)=x22−x+ln⁡|x2+2x+2|2+C\begin{align*} \int\frac{x^3+ x^2+ x -1}{x^2 + 2x + 2}dx & = \int (x-1)dx + \int\frac{x+1}{x^2 + 2x + 2}dx, \qquad \text{(long division)}\\ &= \frac{x^2}{2} - x+ \frac{\ln|x^2 + 2x+2|}{2} + C\\ \end{align*}

  2. ∫4x2−3x−4x3+x2−2xdx=∫4x2−3x−4x(x−1)(x−2)dx\begin{align*} \int \frac{4x^2 - 3x - 4}{x^3+ x^2 -2x}dx &= \int \frac{4x^2 - 3x - 4}{x(x-1)(x-2)}dx \end{align*} and here we write 4x2−3x−4x(x−1)(x−2)=Ax+Bx−1+Cx+2=A(x−1)(x+2)+Bx(x+2)+Cx(x−1)x(x−1)(x+2)=(A+B+C)x2+(A+2B−C)x−2Ax(x−1)(x+2).\begin{align*} \frac{4x^2 - 3x - 4}{x(x-1)(x-2)} &= \frac{A}{x} + \frac{B}{x-1} + \frac{C}{x+2}\\ &= \frac{A(x-1)(x+2) + Bx(x+2) + C x(x-1)}{x(x-1) (x+2)}\\ &= \frac{(A+B+C)x^2 + (A + 2B - C)x - 2A}{x(x-1) (x+2)}. \end{align*} This is the linear system A+B+C=4,A+ B + C = 4,A+2B−C=−3A+ 2B - C = -3and−2A=−4- 2A = -4 which has solution A=2,B=−1,C=3A = 2, B= -1, C = 3. So, ∫4x2−3x−4x3+x2−2xdx=∫4x2−3x−4x(x−1)(x−2)dx=∫2xdx−∫1x−1dx+∫3x+2dx=2ln⁡|x|−ln|x−1|+3ln|x+2|C\begin{align*} \int \frac{4x^2 - 3x - 4}{x^3+ x^2 -2x}dx &= \int \frac{4x^2 - 3x - 4}{x(x-1)(x-2)}dx \\ &=\int\frac{2}{x}dx - \int\frac{1}{x-1}dx + \int\frac{3}{x+2}dx\\ &= 2\ln|x| - ln|x-1| + 3 ln|x+2|_C \end{align*}

  3. Using that x3+4x−1x(x−1)3=Ax+Bx−1+C(x−1)2+D(x−1)3\frac{x^3 + 4x - 1}{x(x-1)^3} = \frac{A}{x} + \frac{B}{x-1}+ \frac{C}{(x-1)^2} + \frac{D}{(x-1)^3} has solution A=1,B=0,C=3,D=−4A= 1, B = 0 , C = 3, D = -4, we find that ∫x3+4x−1x(x−1)3dx=∫1xdx+3∫1(x−1)2dx−4∫1(x−1)3dx=ln⁡|x|−3(x−1)−1+2(x−1)−2+C\begin{align*} \int\frac{x^3 + 4x - 1}{x(x-1)^3}dx &= \int\frac{1}{x}dx + 3\int \frac{1}{(x-1)^2}dx -4\int \frac{1}{(x-1)^3}dx\\ &= \ln|x| - 3(x-1)^{-1} +2(x-1)^{-2}+ C \end{align*} where we have used the substitution u=x−1,du=dxu = x-1, du = dx to integrate the second two terms.

  4. Here, the partial fractions look slightly different because of the irreducible quadratic factor in the denominator 5x3−3x2+2x−1x2(x2+1)=Ax+Bx2+Cx+Dx2+1.\frac{5x^3 - 3x^2 + 2x -1}{x^2(x^2+1)} = \frac{A}{x} + \frac{ B}{x^2} + \frac{Cx+D}{x^2 +1}. Notice, the linear Cx+DCx+D above the quadratic denominator. This is solved the same way as above and we find that A=2,B=−1,C=3,D=−2A = 2, B = -1, C = 3, D = -2, so ∫5x3−3x2+2x−1x2(x2+1)dx=2∫1xdx−∫1x2dx+∫3x−2x2+1dx=2ln⁡|x|+1x+3∫xx2+1−2∫1x2+1dx=2ln⁡|x|+1x+32ln⁡|x2+1|−2arctan⁡x+C\begin{align*} \int\frac{5x^3 - 3x^2 + 2x -1}{x^2(x^2+1)}dx& = 2\int \frac{1}{x}dx - \int\frac{1}{x^2} dx + \int \frac{3x-2}{x^2 + 1} dx\\ & = 2 \ln |x| + \frac{1}{x} + 3\int \frac{x}{x^2 + 1} - 2\int\frac{1}{x^2 + 1}dx\\ & = 2 \ln |x| + \frac{1}{x} + \tfrac{3}{2}\ln|x^2+1| - 2 \arctan x + C \end{align*}

3.6 Non-Elementary Functions

The elementary functions are polynomials, trigonometric, exponential, rational or any combination of these using +,−,×,÷,exp+, -, \times, \div, \exp or composition.

Consider, the function F:ℕ→ℕF:\mathbb{N}\to \mathbb{N} defined by the rule that F(n)=the nth Fibonacci numberF(n) = \text{the } n^{th} \text{ Fibonacci number}. Is FF an elementary function? The answer here is YES! Now, is every function elementary? NO.

For example, f(t):=et2f(t):= e^{t^2} is continuous on ℝ\mathbb{R}, so integrable. Then define F(x):=∫0xet2dtF(x) := \int_0 ^x e^{t^2}dt which has derivative F′(x)=f(x)F'(x) = f(x) (by FTC I). It can be shown that F(x)F(x) is not elementary, meaning you can’t find a formula for F(x)F(x).

4 Applications of integration

4.1 Areas between curves

Consider a region bounded above by y=f(x)y = f(x) and below by y=g(x)y = g(x).

  • A=A1−A2=∫abf(x)dx−∫abg(x)dx=∫ab(f(x)−g(x))dx\begin{align*} A &= A_1- A_2\\ & = \int_a^bf(x)dx - \int_a^b g(x) dx\\ & = \int_a^b(f(x) - g(x))dx \end{align*}

  • A=A1+A2=∫abf(x)dx+(−∫abg(x)dx)=∫ab(f(x)−g(x))dx\begin{align*} A &= A_1+A_2\\ & = \int_a^bf(x)dx + \left(-\int_a^b g(x) dx\right)\\ & = \int_a^b(f(x) - g(x))dx \end{align*}

  • A=A1−A2=−∫abg(x)dx−(−∫abf(x)dx)=∫ab(f(x)−g(x))dx\begin{align*} A &= A_1- A_2\\ & = -\int_a^bg(x) dx -\left(- \int_a^b f(x) dx\right)\\ & = \int_a^b(f(x) - g(x))dx \end{align*}

Notice that in all three cases thus far, we have the area between ff and gg on [a,b][a, b] when f(x)≥g(x)f(x) \geq g(x) is given by the formula ∫ab(f(x)−g(x))dx.\int_a^b (f(x)- g(x) ) dx.

Now, suppose that f(x)≥g(x)f(x)\geq g(x) on [a,c][a, c] and then g(x)≥f(x)g(x) \geq f(x) on [c,b][c, b]. Then

  • A=A1+A2=∫ac(f(x)−g(x))dx+∫cb(g(x)−f(x))dx=∫ab(f(x)−g(x))dx\begin{align*} A &= A_1+ A_2\\ & = \int_a^c(f(x)-g(x)) dx + \int_c^b( g(x) - f(x)) dx\\ & = \int_a^b(f(x) - g(x))dx \end{align*}

Example 15. Find the area of the region bounded by...

  1. Y=xY = x and y=6−x2y = 6-x^2;

    Solution: Since there is no given interval on which to find the area, we must compute where these two curves meet. That is, solve x=y=6−x2x = y = 6-x^2 which is equivalent to 0=(x+3)(x−2)0= (x+3)(x-2) so that these curves meet at x=−3x = -3 and x=2x = 2. On this interval we find that 6−x2≥x6-x^2 \geq x so the area between them is computed by ∫−32(6−x2−x)dx=[6x−x33−x22]|−32=1256\begin{align*} \int_{-3}^2(6- x^2 - x) dx = \left[6x - \frac{x^3}{3} - \frac{x^2}{2}\right]|_{-3}^2 = \tfrac{125}{6} \end{align*}

  2. y=x2y = \tfrac{x}{2} and y2=8−xy^2 = 8 - x. These curves meet when x24=8−x\frac{x^2}{4} = 8 - x which has solutions x=−8x = -8 and x=4x = 4

    Solution 1: Here we integrate along the xx-axis as follows; A=∫−84(x2−(−8−x))dx+2∫488−xdxA = \int_{-8}^4 \left(\frac{x}{2} - (-\sqrt{8 - x})\right)dx + 2\int_4^8 \sqrt{8-x}dx

    Solution 2: If we tilt our heads, this is actually easier done by integrating along the yy-axis. The intersection points are (−8,−4)(- 8, -4) and (4,2)(4, 2) and the area is given by ∫−42(8−y2−2y)dy=(8y−y33−y2)|−42\int_{-4}^2 (8-y^2 - 2y)dy = (8y - \tfrac{y^3}{3} - y^2)|_{-4}^2

4.2 Arc Length of a Parameterized Curve

Let 𝒞\mathcal{C} be the smooth curve obtained obtained by graphing y=f(x)y = f(x) over the interval [a,b)[a, b). For the arc length of 𝒞\mathcal{C} we apply the following simple recipe.

  1. Subdivide the interval (a,b)(a, b) into nn equal subintervals of length Δx=b−ax\Delta x = \frac{b-a}{x}

  2. Let a=x0,…,b=xna = x_0, \dots, b = x_n

  3. Let pip_i be the point (xi,f(xi))(x_i, f(x_i)) on 𝒞\mathcal{C} and d(pi−1,pi)d(p_{i-1}, p_i) be the Euclidean distance between the points pi−1p_{i-1} and pip_i. That is, d(pi−1,pi)=(xi−xi−1)2+(f(xi)−f(xi−1))2=(xi−xi−1)1+(f(xi)−f(xi−1)xi−xi−1)2=Δx1+f′(xi*)2d(p_{i-1}, p_i) = \sqrt{(x_i - x_{i-1})^2 + (f(x_i)- f(x_{i-1}))^2} = (x_i - x_{i-1}) \sqrt{1+ \left(\frac{f(x_i) - f(x_{i-1})}{x_i - x_{i-1}}\right)^2} = \Delta x\sqrt{1 + f'(x_i^*)^2} where the last equality holds by the Mean Value Theorem.

    Hence, now the approximate length of 𝒞\mathcal{C} is given by ∑i=1n1+f′(xi*)2Δx\sum_{i=1}^n \sqrt{1 + f'(x_i^*)^2}\Delta x another Riemann sum! Finally, the arc length of 𝒞\mathcal{C} is given by ℒength(𝒞)=limn→∞∑i=1n1+f′(xi*)2Δx=∫ab1+f′(x)2dx\begin{equation} \label{arclength} \boxed{\mathcal{L}ength(\mathcal{C}) = \lim_{n\to\infty}\sum_{i=1}^n \sqrt{1 + f'(x_i^*)^2}\Delta x = \int_a^b \sqrt{1 + f'(x)^2} dx } \end{equation}(6)

Example 16. Find the length of the curve 𝒞\mathcal{C} defined by y=x3/2y = x^{3/2} on the interval [0,5][0, 5].

Solution: ℒength(𝒞)=∫051+y′(x)2dx=∫051+94xdx=12∫054+9xdx=33527\begin{align*} \mathcal{L}ength(\mathcal{C}) &= \int_0^5\sqrt{1+y\prime(x)^2}dx\\ &= \int_0^5\sqrt{1+\tfrac{9}{4}x}dx\\ &= \frac{1}{2}\int_0^5\sqrt{4+9x}dx = \frac{335}{27}\\ \end{align*}

5 Calculating Volumes

5.1 Cross sectional method

The cross sectional method is often the most practical method used to compute volumes of solids of revolution (a solid obtained by revolving a region bounded by y=f(x)y = f(x) over [a,b][a,b] about the xx- or yy-axis).

Principle behind the cross section method

  1. subdivide [a,b][a,b] into nn equal sub intervals, each of length Δx=b−an\Delta x = \frac{b-a}{n}

  2. Let A(xi)A(x_i) denote the area of the cross section of the solid at xix_i

  3. Then A(x1),A(x2),…A(x_1), A(x_2), \dots is a sequence of areas of cross sections, each a function of xix_i.

  4. If we then keep A(x)A(x) constant over the interval (xi,xi+1)(x_i, x_{i+1}) we obtain an approximation Vn(xi)=A(xi)ΔxV_n(x_i) = A(x_i)\Delta x

  5. We now have a sequence of volumes Vn(x1),Vn(x2),…V_n(x_1) , V_n(x_2), \dots

  6. The nthn^{th} approximation of the volume of this solid is then Vn=∑i=1nVn(xi)=∑i=1nA(xi)ΔxV_n = \sum_{i=1}^n V_n(x_i) = \sum_{i=1}^nA(x_i)\Delta x which is a Riemann sum.

  7. So, theoretically, the actual volume of the solid is V=∫abA(xi)dx=limn→∞∑i=1nA(xi)ΔxV = \int_a^bA(x_i) dx = \lim_{n\to \infty} \sum_{i=1}^n A(x_i)\Delta x

Example 17. Using the cross sectional method to calculate the volume of a square based pyramid, with base b×bb\times b and height h.

Solution: The side length at xx can be found using similar triangles as s(x)=xbhs(x) = \frac{xb}{h}, so then the area at xx is then A(x)=s(x)2=x2b2h2A(x) = s(x)^2 = \frac{x^2 b^2}{h^2}. Now, the volume can be computed by V=∫0hA(x)dx=b2h2∫0hx2dx=b2h2[x33]0h=b2h3V = \int_0^h A(x) dx =\frac{b^2}{h^2} \int_0^hx^2 dx =\frac{b^2}{h^2}\left[ \frac{x^3}{3}\right]_0^h = \frac{b^2h}{3}

Note that this method would also work using the yy-axis and integrating with respect to yy.

The above example was not a solid of revolution. However, there is a nice formula for the cross sectional area (and hence the volume) of a solid of revolution.

Notice, that when y=f(x)y = f(x) is revolved about, say, the xx-axis, the cross sectional area is a circle, of radius f(x)f(x) centred at the xx axis. So then A(x)=πf(x)2A(x) = \pi f(x)^2 (the area of a circle of radius f(x)f(x)). Hence, V=∫abπf(x)2dx\begin{equation} \label{revolution} \boxed{V = \int_a^b \pi f(x)^2 dx} \end{equation}(7)

If this was about the yy-axis then V=∫cdπg(y)dyV = \int_c^d \pi g(y) dy.

Example 18. All of the following are solids of revolution.

  1. Show that the volume of a sphere of radius rr is 43πr3\frac{4}{3}\pi r^3.

    Solution: Here we use the function y=r2−x2y = \sqrt{r^2 - x^2} which is the top half of the circle to be revolved. So then the volume is achieved by integrating A(x)=πy2A(x) = \pi y^2 along the interval [−r,r][-r, r]. That is, V=∫−rrπ(r2−x2)2dx=π∫−rr(r2−x2)dx=π[r2x−x33]−rr=43πr2V = \int_{-r}^r \pi (\sqrt{r^2 - x^2})^2dx =\pi \int_{-r}^r (r^2 - x^2)dx = \pi\left[r^2x - \frac{x^3}{3}\right]_{-r}^r = \frac{4}{3}\pi r^2

  2. Find the volume of a cone with height hh and radius rr.

    Solution: This will be done along the yy-axis, since standing cones make more sense than sideways cones. The relationship between xx and yy here is that y=hrxy = \frac{h}{r}x (which can be thought of as the slope of a cone whose tip is at the origin). So the radius at yy is x=rhyx = \frac{r}{h} y and the volume is then given by V=π∫0h(rhy)2dy=πr2h2∫0hy2dy=πr2h2⋅h33=13πr2hV =\pi \int_0^h\left( \frac{r}{h}y\right)^2dy = \pi \frac{r^2}{h^2} \int_0^h y^2dy = \pi \frac{r^2}{h^2}\cdot \frac{h^3}{3} = \frac{1}{3}\pi r^2 h

Now, we are ready for something slightly more involved.

Example 19. Find the volume of the solid formed by revolving the region bounded by y2=xy^2 = x and y=x3y = x^3 about the (i) xx-axis, (ii) yy-axis, and (iii) the x=−1x = -1 axis.

Notice beforehand that the intersection occurs at (0,0)(0,0) and (1,1)(1,1). So,

  • Revolving about the xx-axis, V=∫01π(x2−(x3)2)dx=π[x22−x77]01=514πV = \int_0^1 \pi(\sqrt{x}^2 - (x^3)^2)dx = \pi\left[\frac{x^2}{2}- \frac{x^7}{7}\right]_0^1 = \frac{5}{14} \pi

  • About the yy-axis, V=∫01π((y3)2−(y2)2)dy=π[35y5/3−y55]01=25πV = \int_0^1\pi\left((\sqrt[3]{y})^2 - (y^2)^2\right)dy = \pi\left[\frac{3}{5}y^{5/3}- \frac{y^5}{5}\right]_0^1 = \frac{2}{5}\pi

  • About x=−1x = -1 axis, we need to readjust the integrand. V=∫01π((y3+1)2−(y2+1)2)dy=π∫01(y2/3+2y1/3+1−y4−2y2−1)dy=π[25y5/2+64y4/3−y55−23y3]01=3730π\begin{align*} V &= \int_0^1\pi\left((\sqrt[3]{y}+1)^2 - (y^2+1)^2 \right)dy \\ &= \pi\int_0^1 \left(y^{2/3}+ 2y^{1/3} + 1 - y^4 - 2y^2 -1\right)dy \\ &= \pi\left[\frac{2}{5}y^{5/2} + \frac{6}{4}y^{4/3} - \frac{y^5}{5} - \frac{2}{3}y^3\right]_0^1\\ = \frac{37}{30}\pi \end{align*}

5.2 Cylindrical Shell Method

The volume of a shell is equal to the outer volume minus the inner volume. Mathematically if r<Rr<R represent the inner and outer radius of the cylinder respectively, then V=outer − inner=πR2h−πr2h=πh(R2−r2)=2πhR+r2(R−r)=2πhR*t\begin{align*} V = \text{outer } - \text{ inner}\\ &= \pi R^2h - \pi r^2h\\ &= \pi h (R^2 - r^2) \\ &= 2\pi h\frac{R+r}{2}(R-r)\\ &= 2\pi h R^* t \end{align*} where R*=R+r2R^* = \frac{R + r}{2} is the average radius and t=R−rt = R-r is the thickness of the shell.

Steps for this method:

  1. Suppose we have a region bounded by y=f(x)y = f(x) an suppose it is revolved about the yy-axis,

  2. Subdivide the interval [a,b][a,b] into nn equal subintervals Δx=b−an\Delta x = \frac{b-a}{n},

  3. Let V(xi)V(x_i) represent the volume of the cylindrical shell with outer radius xix_i, inner radius xi−1x_{i-1} and height f(xi)f(x_i),

  4. then we have a sequence V(x1),V(x2),…V(x_1), V(x_2), \dots of volumes of shells which fill our solid so the approximate volume is ∑i=1nV(xi)=∑i=1n2πf(xi)xi*Δx, where xi*=xi+xi−12\sum_{i=1}^n V(x_i) = \sum_{i=1}^n 2\pi f(x_i) x_i^* \Delta x, \text{ where } x_i^* = \frac{x_i + x_{i-1}}{2} which is approximately ∑i=1n2πxif(xi)Δx\sum_{i=1}^n 2\pi x_i f(x_i) \Delta x a Riemann sum! Then the volume is given by V=limn→∞∑i=1n2πxif(xi)Δx=2π∫abxf(x)dx\begin{equation} \label{shells} \boxed{V = \lim_{n\to \infty} \sum_{i=1}^n 2\pi x_i f(x_i) \Delta x = 2\pi \int_a^b xf(x) dx} \end{equation}(8)

Note: This is most often used when there is a hole punched in the solid.

Example 20. Find the volume of the solid that remains after a hole of radius aa has been bored through the centre of a sphere of radius b(>a)b(>a).

Solution: V=2∫ab2πxb2−a2dx, let x=bsin⁡θ,dx=bcos⁡θ=4π∫x=ax=bb2sin⁡θb2(1−cos⁡2θ)bcos⁡θdθ=4πb3∫x=ax=bsin⁡θcos⁡2θdθ,u=cos⁡θ=4πb3∫x=ax=bu2du=4πb3[u33]x=ax=b\begin{align*} V &= 2\int_a^b2\pi x \sqrt{b^2 - a^2}dx , \quad \text{ let } x = b\sin\theta, dx = b\cos \theta\\ &= 4\pi \int_{x= a}^{x = b}b^2 \sin \theta\sqrt{b^2(1-\cos^2 \theta)} b\cos\theta d\theta\\ &= 4\pi b^3 \int_{x= a}^{x = b}\sin \theta\cos^2\theta d\theta, u = \cos\theta\\ &= 4\pi b^3 \int_{x=a}^{x=b} u^2 du \\ & = 4\pi b^3 \left[\frac{u^3}{3}\right]_{x = a}^{x = b} \end{align*} Now, with u=cos⁡θ=b2−x2bu = \cos\theta= \frac{\sqrt{b^2 - x^2}}{b} we have 4πb3[u33]x=ax=b=4πb3[(b2−x2)3/2b3]x=ax=b=43π(b2−a2)3/24\pi b^3 \left[\frac{u^3}{3}\right]_{x = a}^{x = b} = 4\pi b^3\left[\frac{(b^2-x^2)^{3/2}}{b^3}\right]_{x = a}^{x = b} = \frac{4}{3}\pi(b^2- a^2)^{3/2}

Example 21. Using the method of cylindrical shells, find the volume obtained by revolving the region bounded by y=x2y = x^2 and y2=xy^2 = x about the yy-axis.

Solution: V=∫012πx(x−x3)dx=2π∫01(x3/2−x4)dx=2π[25x5/2−x55]01=25πV = \int_0^12\pi x \left(\sqrt{x} - x^3\right)dx = 2\pi \int_0^1(x^{3/2} - x^4)dx = 2 \pi\left[\frac{2}{5}x^{5/2} - \frac{x^5}{5}\right]_0^1 = \frac{2}{5}\pi

In general we have obtained the following two formulas V=∫abπf(x)dx and V=∫ab2πxf(x)dx\boxed{V = \int_a^b \pi f(x) dx \text{ and } V = \int_a^b 2\pi x f(x)dx}

6 Numerical Approximation

This is used to approximate definite integrals when they cannot be integrated.

There are 3 common methods:

  1. Midpoint Rule: Given ∫abf(x)dx=lim⁡n→∞∑i=1nf(xi)Δx\int_a^b f(x) dx = \lim_{n\to \infty } \sum_{i=1}^n f(x_i)\Delta x, recall that we had a choice of sample points xix_i in the interval (xi−1,xi)(x_{i-1}, x_{i}) and we have just been using the right hand side of the interval. Now, consider Rn=∑i=1nf(xi)Δx−The right-hand approximationR_n = \sum_{i=1}^n f(x_i)\Delta x\quad - \quad\text{The right-hand approximation} Ln=∑i=1nf(xi−1)Δx−The left-hand approximationL_n = \sum_{i=1}^n f(x_{i-1})\Delta x\quad - \quad\text{The left-hand approximation} and finally Mn=∑i=1nf(mi)Δx−The Midpoint approximation\boxed{M_n = \sum_{i=1}^n f(m_i)\Delta x \quad - \quad\text{The Midpoint approximation}} where mi=xi−1+xi2m_i = \frac{x_{i-1} + x_i}{2}

  2. Trapezoidal Rule: Here we use Tn=Ln+Rn2=12[∑i=1nf(xi−1)Δx+∑i=1nf(xi)Δx]=Δx2[f(x0)+2f(x1)+…+2f(xn−1)+f(xn)]\boxed{T_n = \frac{L_n + R_n}{2} = \frac{1}{2}\left[\sum_{i=1}^n f(x_{i-1})\Delta x + \sum_{i=1}^n f(x_{i})\Delta x\right] = \frac{\Delta x}{2}\left[f(x_0) + 2f(x_1) +\dots + 2f(x_{n-1}) + f(x_n) \right]}

  3. Simpson’s Rule: Here we use 2n2n sample points x1,x2,…,xn,…,x2nx_1, x_2, \dots, x_n, \dots, x_{2n}, but our intervals remain of size Δx=b−an\Delta x = \frac{b-a}{n}

    S2n:=13[2Mn+Tn]\boxed{S_{2n} := \frac{1}{3} \left[2M_n + T_{n}\right]} Now, Mn=2Δx[∑i=1nf(x2i−1)]M_n = 2\Delta x\left[\sum_{i = 1} ^{n} f(x_{2i-1})\right] because midpoints here are the odd indexed sample points and T2n=2Δx2(f(x0)+2f(x2)+…2f(x2n−2)+f(x2n))T_{2n} = 2\frac{\Delta x}{2}\left(f(x_0) + 2f(x_2) + \dots 2f(x_{2n-2}) + f(x_{2n})\right) So,

    S2n=Δx3[4∑i=1nf(x2i−1)+(f(x0)+2f(x2)+…2f(x2n−2)+f(x2n))]=Δx3(f(x0)+4f(x1)+2f(x2)+4f(x3)+…+4f(x2n−1)+f(x2n))\begin{align*} S_{2n} &= \frac{\Delta x}{3}\left[4\sum_{i = 1} ^{n} f(x_{2i-1}) +(f(x_0) + 2f(x_2) + \dots 2f(x_{2n-2}) + f(x_{2n}))\right]\\ &= \frac{\Delta x}{3}\left(f(x_0) + 4f(x_1) + 2f(x_2) + 4f(x_3) + \dots + 4f(x_{2n-1}) + f(x_{2n})\right) \end{align*}

Example 22. Approximate the definite integral ∫03x2dx\int_0^3 x^2 dx with n=6n = 6 (i.e. so that Δx=3−06=.5\Delta x= \frac{3 - 0 }{6 } = .5 using; (i) midpoint rule, (ii) trapezoid rule, (iii) Simpson’s rule.

Solution:

  • For this, we need the following table of values:

    nn mim_i f(mi)f(m_i)
    1 .25 0.0625
    2 .75 0.5625
    3 1.25 1.5625
    4 1.75 3.0625
    5 2.25 5.0625
    6 2.75 7.5625

    So, Mn=∑i=16f(mi)Δx=12(19.875)=8.9375\begin{align*} M_n &= \sum_{i=1}^6 f(m_i)\Delta x = \frac{1}{2}(19.875)= 8.9375 \end{align*}

  • Tn=Δx2(f(0)+2f(0.5)+2f(1)++…+2f(5.5)+f(6))=14(02+2(0.5)2+…+32)=9.125\begin{align*} T_n &= \frac{\Delta x}{2}(f(0) + 2f(0.5)+ 2f(1) + + \dots + 2f(5.5) + f(6)) \\ &= \frac{1}{4}( 0^2 + 2(0.5)^2 + \dots + 3^2)\\ & = 9.125 \end{align*}

  • Sn=Δx3(02+4(0.5)2+2(1)2+4(1.5)2+2(2)2+4(2.5)2+32)=16(54)=9\begin{align*} S_n = \frac{\Delta x } {3} (0^2 + 4(0.5)^2 + 2(1)^2 + 4(1.5)^2 + 2(2)^2 + 4(2.5)^2 + 3^2) = \frac{1}{6}(54) = 9 \end{align*}

6.1 Error bounds on approximations

Here we will just provide the error bounds without examining the required analysis.

For MnM_n; the error bound is |E(Mn)|≤k(b−a)324n2\boxed{|E(M_n)| \leq \frac{k(b-a)^3}{24n^2}} where k=max⁡x∈(a,b){f″(x)}k = \max_{x\in (a,b)}\{f''(x)\}.

For TnT_n: Error is |E(Tn)|≤k(b−a)312n2,k=maxx∈(a,b){f″(x)}\boxed{|E(T_n)| \leq \frac{k(b-a)^3}{12 n^2},\qquad k = \max_{x\in (a,b)}\{f''(x)\}}

For SnS_n; Error is |E(Sn)|≤k(b−a)5180n4,k=maxx∈(a,b){f(4)(x)}.\boxed{|E(S_n)| \leq \frac{k (b-a)^5}{180n^4}, \qquad k = \max_{x\in (a,b)}\{f^{(4)}(x)\}.}

Example 23. Estimate the error bound when using T10T_{10} or S10S_{10} approximation for ∫121xdx\int_1^2 \frac{1}{x}dx.

Solution: Note that d2dx2(1x)=2x3\frac{d^2}{dx^2}\left(\frac{1}{x}\right) = \frac{2}{x^3} and d4dx4(1x)=d2dx2(2x3)=ddx(−6x4)=24x5\frac{d^4}{dx^4}\left(\frac{1}{x}\right) = \frac{d^2}{dx^2}\left(\frac{2}{x^3}\right) = \frac{d}{dx}\left(\frac{-6}{x^4}\right) =\frac{24}{x^5} so that the constant kk for T10T_{10} is kT=max[1,2](2x3)=2k_T = \max_{[1,2]} \left(\frac{2}{x^3}\right) = 2 and for S10S_{10} is kS=max[1,2](24x5)=24.k_S = \max_{[1,2]} \left(\frac{24}{x^5}\right) = 24. Now, |E(T10)|≤kT(2−1)312(10)2=1600|E(T_{10})| \leq \frac{k_T(2-1)^3}{12(10)^2} = \frac{1}{600} and |E(S10)|≤kS(2−1)5180(10)4=241800000.|E(S_{10})| \leq \frac{k_S(2-1)^5}{180(10)^4} = \frac{24}{1800000}.

7 Improper Integrals

The following integrals ∫a∞f(x)dx=limb→∞∫abf(x)dx OR ∫−∞af(x)dx=limb→−∞f(x)dx\int_a^\infty f(x)dx = \lim_{b\to \infty} \int_a^bf(x)dx \text{ OR } \int_{-\infty}^af(x)dx = \lim_{b\to -\infty}f(x)dx are called improper. Similarly, ∫−∞∞f(x)dx=∫−∞af(x)dx+∫a∞f(x)dx\int_{-\infty}^\infty f(x)dx = \int_{-\infty}^af(x)dx + \int_a^\infty f(x)dx is improper (provided, both limits exist).

Warning: Do not do ∫−∞∞f(x)dx=lim⁡t→∞∫−ttf(x)dx\int_{-\infty}^\infty f(x)dx = \lim_{t\to \infty}\int_{-t}^t f(x)dx, since one may not converge.

Example 24. Evaluate the improper integral ∫−∞∞11+x2dx\int_{-\infty}^\infty \frac{1}{1+ x^2}dx.

Solution: ∫−∞∞11+x2dx=limb→−∞∫b011+x2dx+limt→∞∫0t11+x2dx=limb→−∞[arctanx]b0+limt→∞[arctanx]0t=(0−−π2)+(π2−0)=π\begin{align*} \int_{-\infty}^\infty \frac{1}{1+x^2}dx & = \lim_{b\to -\infty}\int_b^0 \frac{1}{1+x^2}dx + \lim_{t\to \infty}\int_0^t\frac{1}{1+x^2}dx\\ &= \lim_{b\to -\infty}\left[\arctan x\right]_b^0 + \lim_{t\to \infty}\left[\arctan x\right]_0^t\\ &= \left(0 - \frac{-\pi}{2}\right) + \left(\frac{\pi}{2} - 0\right)\\ &= \pi \end{align*}

7.1 Improper integrals of another type

Suppose the function ff is defined only on the interval (a,b](a, b] with no specified value at aa. Then we can still define the definite integral ‘improperly’ as ∫abf(x)dx=limt→a−∫tbf(x)dx.\int_a^bf(x)dx = \lim_{t\to a^-} \int_t^bf(x)dx. The same can be done when f(x)f(x) is defined on [a,b)[a, b), or even if, say f(x)f(x) is only defined on [a,c)∪(c,b][a, c)\cup (c, b] (with a hole in the middle of the interval), then ∫abf(x)dx=limt→c−∫atf(x)dx+limt→c+∫tbf(x)dx\int_a^b f(x)dx = \lim_{t\to c^-} \int_a^tf(x)dx + \lim_{t\to c^+}\int_t^bf(x)dx Note that the above integral will only converge if both limits exist.

Example 25.

Proposition 1. [Comparison test for improper integrals] Suppose that f(x)≥g(x)f(x)\geq g(x) on [a,∞)[a, \infty). If ∫a∞f(x)dx\int_a^\infty f(x)dx converges, then ∫a∞g(x)dx\int_a^\infty g(x) dx also converges.

Furthermore, if ∫a∞g(x)dx\int_a^\infty g(x) dx diverges, then so does ∫a∞f(x)dx\int_a^\infty f(x)dx.

Example 26. Does ∫0∞e−x2dx\int_0^\infty e^{-x^2}dx converge?

Soloution: We have x2≥xx^2\geq x on [1,∞][1, \infty] so ex2≥exe^{x^2}\geq e^x on [1,∞)[1,\infty) or 1ex2≤1ex\frac{1}{e^{x^2}}\leq \frac{1}{e^x}. So ∫0∞e−x2dx=∫01e−x2dx+∫1∞e−x2dx≤∫01e−x2dx+∫1∞e−xdx=∫01e−x2dx+limt→∞∫1te−xdx=∫01e−x2dx+limt→∞[−e−t−(−e−1)]=∫01e−x2dx+e<∞\begin{align*} \int_0^\infty e^{-x^2} dx &= \int_0^1e^{-x^2}dx + \int_1^\infty e^{-x^2}dx\\ &\leq \int_0^1e^{-x^2}dx + \int_1^\infty e^{-x}dx\\ &= \int_0^1e^{-x^2}dx + \lim_{t\to \infty}\int_1^te^{-x}dx\\ &= \int_0^1e^{-x^2}dx + \lim_{t\to \infty}\left[-e^{-t} - (-e^{-1})\right]\\ & = \int_0^1e^{-x^2}dx + e <\infty \end{align*} so our integral converges by comparison test.

8 Differential Equations

A differential equation (DE) is an equation which contains a derivative expression. The order of a DE is the highest derivative which appears in the equation.

Example 27. xy″(x)=sin⁡xey(x)x y''(x) = \sin xe^{y(x)} is order 2.

Another, simpler, DE is y′(x)=sin⁡x+exy'(x) = \sin x + e^x. This is easy to solve (integrate both sides), y(x)=−cos⁡x+ex+Cy(x) = - \cos x + e^x + C is a solution.

Lets see a more exciting example.

Example 28. Let P(t)P(t) be a population function (with tt for time). After studying the population over time, and discovering a proportionality amongst the P(t)P(t) and its derivative. That is to say P′(t)=kP(t)P'(t) = k P(t), for some constant kk. The goal now, is to obtain a formula for P(t)P(t). Rearranging slightly is P′(t)P(t)=k⇒∫P′(t)P(t)dt=∫kdt⇔ln⁡|P(t)|=kt+Celn⁡P(t)=ekt+CP(t)=ekteCP(t)=C′ekt\begin{align*} \frac{P'(t)}{P(t)} = k & \Rightarrow \int \frac{P'(t)}{P(t)} dt = \int k dt\\ &\Leftrightarrow \ln |P(t)| = kt+C\\ & e^{\ln P(t)} = e^{kt+C}\\ & P(t) = e^{kt}e^C\\ &P(t) = C'e^{kt} \end{align*} for some positive constant CC that is determined by specified initial conditions (such as P(0)=100P(0) = 100).

Example 29. Verify that y=x2ln⁡xy = x^2\ln x is a solution to x2y″−3xy′+4y=0x^2y'' - 3xy' + 4y = 0 in the region x>0x>0.

Solution: With y=x2ln⁡xy = x^2\ln x, we compute y′=2xln⁡x+xy' = 2x\ln x + x and y″=2ln⁡x+2+1y'' = 2\ln x + 2+ 1. Substituting into the DE, we find x2y″−3xy′+4y=x2(2ln⁡x+3)−3x(2xln⁡x+x)+4x2ln⁡x=2x2ln⁡x+3x3−6x2ln⁡x−3x2+4x2ln⁡x=0\begin{align*} x^2y'' - 3xy' + 4y &= x^2( 2\ln x + 3) - 3x(2x\ln x + x) + 4x^2\ln x\\ &= 2x^2 \ln x + 3x^3 - 6x^2 \ln x - 3x^2 + 4x^2\ln x\\ &= 0 \end{align*}

A particular solution to a DE is one without arbitrary constants. That is, any particular function satisfying the DE. The solution y=x2ln⁡xy = x^2\ln x from the previous is example is a particular solution.

Example 30. Suppose we want a solution to y′+2y=e−xy' + 2y = e^{-x} with y(0)=3y(0) = 3 [This is called an initial value problem].

Check that y=e−x+Ce−2xy = e^{-x} + Ce^{-2x} is a general solution. Indeed, y′=−e−x−2Ce−2xy' = - e^{-x}- 2Ce^{-2x} and −e−x−2Ce−2x+2(e−x+Ce−2x=0.- e^{-x}- 2Ce^{-2x} + 2(e^{-x} + C e^{-2x} = 0. Now since y(0)=3y(0) = 3, we can solve for the constant CC as 3=e0+Ce0=1+C⇒C=23 = e^{0} + Ce^{0} = 1 + C \Rightarrow C = 2 so that y=e−x+2e−2xy = e^{-x} + 2e^{-2x} is a particular solution to the initial value problem (IVP).

8.1 Separable Differential Equations

If a DE can be expressed in the form y′=g(x)f(y)y' = g(x) f(y), we say it is separable. Equivalently 1f(y)dydx=g(x)⇔1f(y)dy=g(x)dx.\frac{1}{f(y)} \frac{dy}{dx} = g(x) \Leftrightarrow \frac{1}{f(y)} dy = g(x) dx.

A separable DE is solved by integrating both sides of this rearrangement. ∫1f(y)dy=∫g(x)dx,\int \frac{1}{f(y)} dy = \int g(x) dx, but this requires some justification: If we are given a DE of the form N(y)dy=M(x)dxN(y)dy = M(x)dx or equivalently N(y)dydx−M(x)=0N(y) \frac{dy }{dx} - M(x) = 0. Now let H1(y)H_1(y) be an anti-derivative of N(y)N(y) and H2(x)H_2(x) an anti-derivative of M(x)M(x). This equation is then equivalent to the following: H1′(y)dydx−H2′(x)=0ddx(H1(y))−H2′(x)=0=ddx(H1(y)−H2(x)))=0\begin{align*} &H'_1(y) \frac{dy}{dx} - H'_2(x) = 0\\ &\frac{d}{dx}(H_1(y)) - H'_2(x) = 0\\ & = \frac{d}{dx}\left(H_1(y) - H_2(x) )\right)= 0 \end{align*} Now, this implies that H1(y)−H2(x)=KH_1(y) - H_2(x) = K (is constant) and we can find y(x)y(x) from H2(y)H_2(y).

Example 31. Is dydx=3x2+4x+22(y−1)\frac{dy}{dx} = \frac{3x^2 + 4x + 2}{2(y-1)} separable? If so, solve it.

Solution: Yes, it is solvable and it can be re-expressed as 2(y−1)dy=(3x2−4x+2)dx⇒2∫(y−1)dy=∫(3x2−4x+2)dx.2(y-1)dy = (3x^2 - 4x + 2)dx \Rightarrow 2\int(y-1)dy = \int(3x^2 - 4x + 2)dx. This integrates to y2−2y=x3+2x2+2x+C.y^2 - 2y = x^3 + 2x^2 + 2x + C. Now, although this is separable an we managed to integrate it, we find that the solution cannot be explicitly expressed as y=⋯y = \cdots. In attempt to extract an explicit solution, we treat this as a quadratic equation in yy. y2−2y−(x3+2x2+2x+C)=0y^2 - 2y - (x^3 + 2x^2 + 2x + C) = 0 which has solutions, y=2±4−4(−1)(x3+2x2+2x+C)2=1±x3+2x2+2x+1+C.y = \frac{2\pm \sqrt{4 - 4(-1)(x^3 + 2x^2 + 2x + C)}}{2} = 1\pm\sqrt{x^3 + 2x^2 + 2x +1+ C}. If we had been given the IVP of y(0)=−1y(0) = -1, then this would imply that the solution be y=1−x3+2x2+2x+1+Cy = 1-\sqrt{x^3 + 2x^2 + 2x +1+ C}.

8.2 Linear Differential Equations

A linear differential equation is most generally expressed as y′+p(x)y=q(x)\begin{equation} \label{LDE} y' + p(x) y = q(x) \end{equation}(9)

Theorem 6. The solution to the linear differential equation (9) is y=1I(x)∫I(x)q(x)dxy = \frac{1}{I(x)} \int I(x) q(x) dx where I(x)=e∫p(x)dxI(x) = e^{\int p(x) dx}.

This function I(x)I(x) is called the integrating factor and is a function satisfying that I(x)(y′+p(x)y)=(I(x)y)′.I(x) \left(y ' + p(x) y\right) = \left(I(x) y\right)'.

Proof. First, verifying that I(x)=e∫p(x)dxI(x) = e^{\int p(x)dx} satisfies the above claimed equation. Indeed, expanding the right by the product rule, we have I(x)(y′+p(x)y)=(I(x)y)′=I′(x)y+I(x)y′⇔I(x)p(x)y=I′(x)yI(x) \left(y ' + p(x) y\right) = \left(I(x) y\right)' = I'(x) y + I(x)y' \Leftrightarrow I(x) p(x) y = I'(x) y so that, provided I(x)≠0I(x)\neq 0, p(x)=I′(x)I(x)p(x) = \frac{I'(x)}{I(x)}. Integrating this says that ∫p(x)dx=∫I′(x)I(x)dx⇔ln⁡|I(x)|=∫p(x)dx⇔I(x)=e∫p(x)dx.\int p(x) dx = \int\frac{I'(x) }{I(x)} dx \Leftrightarrow \ln|I(x)| = \int p(x) dx \Leftrightarrow I(x) = e^{\int p(x) dx}.

Now, that this holds, the left hand side of our DE is expressed as (I(x)y)′(I(x)y)' and now reads, (I(x)y)=q(x)(I(x)y) = q(x). Hence, integrating this, I(x)y=∫q(x)dxI(x)y = \int q(x) dx so y=1I(x)∫I(x)q(x)dxy = \frac{1}{I(x)} \int I(x) q(x) dx as claimed. ◻

Note that this method of solving a DE requires it be of first order (i.e. linear).

Example 32.

  1. Solve the IVP y′−2xy=1y' - 2xy = 1 with y(0)=1y(0) =1.

    Solution: The integrating factor here is I(x)=e−∫2xdx=e−x2I(x) = e^{-\int 2 x dx} = e^{-x^2}, so y=1e−x2∫e−x2dx=ex2(∫0xe−t2dt+C)=ex2∫axe−t2dt+Cex2y = \frac{1}{e^{-x^2}} \int e^{-x^2}dx = e^{x^2}\left(\int_{0}^x e^{-t^2}dt + C\right) = e^{x^2}\int_{a}^x e^{-t^2}dt +C e^{x^2} and with y(0)=1y(0)= 1 we find CC as 1=e0∫00e−t2dt+e0C⇒C=11 = e^0 \int_0^0 e^{-t^2}dt + e^{0}C \Rightarrow C =1

  2. Solve the IVP (y−xsin⁡x)dx+xdy=0(y-x\sin x) dx + x dy = 0 with y(π)=3y(\pi) =3.

    Solution: This is equivalent to y=xsin⁡x+xy′=0y = x\sin x + x y' = 0 or, better, y′+1xy=sin⁡xy'+ \frac{1}{x}y = \sin x. For the integrating factor I(x)=e∫1xdx=eln⁡|x|=|x|I(x) = e^{\int \frac{1}{x} dx} = e^{\ln |x|} = |x|. Now, y=1|x|∫|x|sin⁡xdx,=1x[−xcosx+∫cosxdx],IBP with u=x,dv=sin⁡xdx=−cos⁡x+sin⁡xx+Cx\begin{align*} y &= \frac{1}{|x|} \int|x| \sin x dx, \\ &= \frac{1}{x}\left[-x \cos x + \int \cos xdx\right], \qquad \text{IBP with } u = x, dv = \sin x dx\\ &= -\cos x + \frac{\sin x}{x} + \frac{C}{x} \end{align*}

9 Sequences and Series

Recall, the limit of a sequence: A sequence {xn}\{x_n\} converges to LL if for all ϵ>0\epsilon>0, there exists k∈ℕk\in \mathbb{N} such that |xn−L|<ϵ|x_n - L| <\epsilon for all n>kn>k.

Example 33. an=(−1)ncos⁡nn2a_n = (-1)^n \frac{\cos n}{n^2} and |(−1)ncos⁡nn2|≤1n2→0\left|(-1)^n\frac{\cos n}{n^2}\right|\leq \frac{1}{n^2}\to 0 and by squeeze theorem, an→0a_n\to 0.

An increasing (decreasing) sequence is one such that an+1≥(≤)ana_{n+1}\geq(\leq) a_n for all n≥1n\geq 1. A monotonic sequence is one which is either strictly increasing or decreasing.

Theorem 7 (Monotone sequence theorem). A bounded monotonic sequence always has a limit (i.e. will always converge).

9.1 Series

Let ana_n be a sequence, then ∑n=1∞=a1+a2+a3+…\sum_{n=1}^\infty = a_1 + a_2 + a_3+ \dots is an infinite series. The nthn^{th} partial sum of a series is Sn=∑k=1nakS_n = \sum_{k=1}^n a_k. To evaluate an infinite series we use the limit of the partial sums: ∑n=1∞an=limn→∞Sn=limn→∞∑k=1nak.\sum_{n=1}^\infty a_n = \lim_{n\to \infty} S_n = \lim_{n\to \infty} \sum_{k=1}^n a_k. If the limit exists, series converges. If limit does not exist, series diverges.

Warning: When discussing series, say ∑n=1∞cn\sum_{n=1}^\infty c_n, there are two sequences in play. We have the sequence itself cnc_n and the partial sums SnS_n, so remember ∑n=1∞=limn→∞Sn.\sum_{n=1}^\infty = \lim_{n\to \infty} S_n.

Example 34. ci=i⇒∑n=1∞n=limn→∞∑k=1nk=limn→∞n(n+1)2=∞, (diverges)c_i = i\Rightarrow \sum{n=1}^\infty n = \lim_{n\to \infty} \sum_{k=1}^n k = \lim_{n\to \infty}\frac{n(n+1)}{2} = \infty, \text{ (diverges)}

Consider the geometric series ∑n=1∞arn−1=a+ar+ar2+…+arn+….\sum_{n=1}^\infty a r^{n-1} = a + ar + ar^2 + \dots + ar^n + \dots. The partial sums are given by Sn=a+ar+ar2+…+arn−1S_n = a + ar + ar^2 + \dots + ar^{n-1} and multiplying by rr says, rSn=ar+ar2+…+arn.r S_n = ar + ar^2 + \dots + ar^n. Subtracting these, we have Sn−rSn=a−arn⇔Sn(1−r)=a(1−rn)S_n - rS_n = a - ar^n \Leftrightarrow S_n(1 - r)= a(1-r^n) so that Sn=1(1−rn)1−r.S_n = \frac{1(1-r^n)}{1-r}. Now, when does a geometric series converge? We must have that lim⁡n→∞a(1−rn)1−r\lim_{n\to \infty} \frac{a(1-r^n)}{1-r} exists, which means, in order for a geometric series to converge we must have |r|<1|r|<1.

Furthermore, if |r|<1|r|<1, then the limit can be computed exactly as lim⁡n→∞a(1−rn)1−r=a1−r\lim_{n\to \infty} \frac{a(1-r^n)}{1-r} = \frac{a}{1-r}. That is, the sum a geometric series is ∑n=1∞arn−1={a1−r,|r|<1∞,|r|≥1\sum_{n=1}^\infty ar^{n-1} = \begin{cases} \frac{a}{1-r}, |r|<1\\ \infty, |r|\geq 1\end{cases}

Example 35. Express the repeating decimal 1.231¯1.2\overline{31} as an infinite series and then as a fraction.

Solution: We have 1.231¯=1.2+31103+31103⋅1102+31103⋅1(102)2+…1.2\overline{31} = 1.2 + \frac{31}{10^3} + \frac{31}{10^3}\cdot \frac{1}{10^2} +\frac{31}{10^3}\cdot \frac{1}{(10^2)^2 } + \dots

Letting a=31103a= \frac{31}{10^3} and r=1102<1r = \frac{1}{10^2}<1, so that 1.231¯=1.2+∑n=1∞arn−1=1210+31103⋅11−1102=1219990.1.2\overline{31} = 1.2 + \sum_{n=1}^\infty ar^{n-1} = \frac{12}{10} + \frac{31}{10^3} \cdot \frac{1}{1 - \frac{1}{10^2}} = \frac{1219} {990}.

Theorem 8. Suppose ∑n=1∞cn=L\sum_{n=1}^\infty c_n = L and ∑n=1∞bn=M\sum_{n=1}^\infty b_n = M and let k∈ℝk\in \mathbb{R}. Then, ∑n=1∞kcn=kL\sum_{n=1}^\infty kc_n = k L and ∑n=1∞(cn+bn)=L+M.\sum_{n=1}^\infty (c_n + b_n) = L + M. Note that this theorem requires that both converge.

Theorem 9. If the series ∑n=1∞cn\sum_{n=1}^\infty c_n converges, then the sequence cnc_n must converge to 0.

Proof. Given that ∑n=1∞cn=L\sum_{n=1}^\infty c_n = L, consider the sequence SnS_n of partial sums. Observe, that for each nn, cn=sn−Sn−1c_n = s_n - S_{n-1} and now, limn→∞cn=limn→∞Sn−Sn−1=L−L=0.\lim_{n\to \infty} c_n = \lim_{n\to \infty} S_n - S_{n-1} = L - L = 0. ◻

9.2 Divergence test

Suppose that ∑n=1∞cn\sum_{n=1}^\infty c_n is a series. If lim⁡n→∞cn≠0\lim_{n\to \infty} c_n \neq 0 then the series diverges. This is just the converse of the previous result. Otherwise, divergence test provides no information.

Example 36. Discuss the convergence/divergence of the series

  1. ∑n=1∞(3n+54n)\sum_{n=1}^\infty\left(\frac{3}{n} + \frac{5}{4^n}\right).

    Solution: ∑n=1∞(3n+54n)=∑n=1∞3n+∑n=1∞54n=3∑n=1∞1n⏟diverges+∑n=1∞54(14)n−1⏟converges(geometricr=1/4)\begin{align*} \sum_{n=1}^\infty\left(\frac{3}{n} + \frac{5}{4^n}\right) & = \sum_{n=1}^\infty \frac{3}{n}+ \sum_{n=1}^\infty \frac{5}{4^n}\\ & = 3\underbrace{\sum_{n=1}^\infty \frac{1}{n}}_{diverges}+ \underbrace{\sum_{n=1}^\infty \frac{5}{4}\left(\frac{1}{4}\right)^{n-1}}_{converges (geometric\,r=1/4)}\\ \end{align*} Therefore, the series diverges.

  2. ∑n=1∞1(2n+1)(2n−1)\sum_{n=1}^\infty \frac{1}{(2n+1)(2n-1)}

    Solution: By partial fractions, we find

    ∑n=1∞1(2n+1)(2n−1)=∑n=1∞(−12(2n+1)+12(2n−1))=limn→∞−16+12−110+16−114+110+…+12(12n−1−12n+1)=limn→∞12−12(2n−1)=12\begin{align*} \sum_{n=1}^\infty \frac{1}{(2n+1)(2n-1)} & = \sum_{n=1}^\infty\left( \frac{-1}{2(2n+1)} + \frac{1}{2(2n-1)}\right)\\ &= \lim_{n\to \infty} - \frac{1}{6} + \frac{1}{2} - \frac{1}{10} + \frac{1}{6} - \frac{1}{14} + \frac{1}{10} + \dots + \frac{1}{2}\left(\frac{1}{2n-1} - \frac{1}{2n+1}\right) \\ & = \lim_{n\to \infty}\frac{1}{2} - \frac{1}{2(2n-1)} = \frac{1}{2} \end{align*} This is a telescoping series.

Theorem 10 (Integral test for convergence of a series). Let ∑n=1∞cn\sum_{n=1}^\infty c_n be a series and suppose f(x)f(x) is a function on [1,∞)[1, \infty) such that

  1. f(x)>0f(x) > 0 on [1,∞)[1,\infty).

  2. f(x)f(x) is continuous on [1,∞)[1, \infty)

  3. f(x)f(x) is non-increasing on [1,∞)[1, \infty) (i.e. f′(x)≤0f'(x) \leq 0)

  4. f(n)=cnf(n) = c_n for all nn.

Then, ∑n=1∞cn converges ⇔∫1∞f(x)dx converges.\sum_{n=1}^\infty c_n \text{ converges } \Leftrightarrow \int_1^\infty f(x)dx\text{ converges}.

Proof. Suppose that ∑n=1∞cn\sum_{n=1}^\infty c_n converges and show that ∫1∞f(x)dx\int_1^\infty f(x)dx converges. Certainly Sn=c1+c2+…+cn≥∫1nf(x)dxS_n = c_1+ c_2 + \dots + c_n\geq \int_1^n f(x)dx so S=limn→∞Sn≥∫1∞f(x)dxS = \lim_{n\to \infty} S_n \geq \int_1^\infty f(x)dx which implies convergence.

Suppose now that ∫1∞f(x)dx\int_1^\infty f(x)dx converges and show the converse. Observe that c2+c3+…+cn≤∫1∞f(x)dxc_2 + c_3+ \dots + c_n \leq \int_1^\infty f(x)dx so Sn=c1+c2+…cn≤c1+∫1∞f(x)dxS_n = c_1+c_2 + \dots c_n \leq c_1 + \int_1^\infty f(x)dx and hence lim⁡n→∞Sn≤c1+∫1∞f(x)dx<∞\lim_{n\to \infty} S_n \leq c_1 + \int_1^\infty f(x)dx< \infty so converges. ◻

9.3 Estimating the value of a series

Suppose that ∑n=1∞cn\sum_{n=1}^\infty c_n is a series proved to be convergent by the integral test (say ∑n=1∞cn=S\sum_{n=1}^\infty c_n = S).

We would like to approximate SS by the partial sums SnS_n and determine what the error will be. Let Rn=S−SnR_n = S- S_n be the remainder (Note that, we are assuming that our cnc_n’s are positive so that the partial sums are an increasing sequence). So, also Rn=S−Sn=(c1+c2+…+cn+…)−(c1+c2+…+cn)=cn+1+cn+2+…R_n = S - S_n = (c_1+ c_2 + \dots + c_n + \dots )- (c_1 + c_2 + \dots + c_n) = c_{n+1} + c_{n+2} + \dots and we claim that ∫n+1∞f(x)dx≤Rn≤∫n∞f(x)dx\int_{n+1}^\infty f(x)dx \leq R_n \leq \int_n^\infty f(x)dx for f(n)=cnf(n) = c_n.

First, it is easy to see that Rn=cn+1+cn+2+…≤∫n∞f(x)dxR_n = c_{n+1} + c_{n+2} + \dots \leq \int_n^\infty f(x)dx. Now, also Rn≥∫n+1∞f(x)dxR_n\geq \int_{n+1}^\infty f(x)dx since these rectangles are an over approximation of the integral.

Now, ∫n+1∞f(x)dx≤Rn≤∫n∞f(x)dxSn+∫n+1∞f(x)dx≤Sn+Rn≤Sn+∫n∞f(x)dxSn+∫n+1∞f(x)dx≤S≤Sn+∫n∞f(x)dx\begin{align*} \int_{n+1}^\infty f(x)dx \leq &R_n \leq \int_n^\infty f(x)dx\\ S_n + \int_{n+1}^\infty f(x)dx \leq &S_n +R_n \leq S_n + \int_n^\infty f(x)dx\\ S_n + \int_{n+1}^\infty f(x)dx \leq &S \leq S_n + \int_n^\infty f(x)dx\\ \end{align*} So we know that SS lies in the interval [Sn+∫n+1∞f(x)dx,Sn+∫n∞f(x)dx]\left[S_n + \int_{n+1}^\infty f(x)dx, S_n + \int_n^\infty f(x)dx\right] and the error cannot be more than the length of the interval. That is, |Error|≤(Sn+∫n∞f(x)dx)−(Sn+∫n+1∞f(x)dx)=∫n∞f(x)dx−∫n+1∞f(x)dx=∫nn+1f(x)dx\boxed{|\text{Error}| \leq ( S_n + \int_n^\infty f(x)dx) - (S_n + \int_{n+1}^\infty f(x)dx) =\int_n^\infty f(x)dx - \int_{n+1}^\infty f(x)dx = \int_n^{n+1}f(x)dx}

Example 37. Use S10S_{10} to help calculate ∑n=1∞1n4\sum_{n=1}^\infty \frac{1}{n^4}.

Solution: With a calculator we find S10=1.082036583S_{10} = 1.082036583. Notice that 1x4\frac{1}{x^4} is continuous, decreasing on [1,∞)[1, \infty) and matches the values of the sequence. So, a good approximation is the midpoint of the interval [S10+∫11∞1x4dx,S10+∫10∞1x4dx]\left[S_{10} + \int_{11}^\infty \frac{1}{x^4}dx, S_{10} + \int_{10}^\infty \frac{1}{x^4}dx\right]. That is, S≈2S10+∫11∞1x4dx+∫10∞1x4dx2≈1.082328469S \approx \frac{2S_{10} + \int_{11}^\infty \frac{1}{x^4}dx+ \int_{10}^\infty \frac{1}{x^4}dx}{2} \approx 1.082328469

9.4 p-series

Any series of the form ∑n=1∞1np\sum_{n=1}^\infty \frac{1}{n^p} where pp is a fixed positive number.

Theorem 11. If ∑n=1∞1np\sum_{n=1}^\infty \frac{1}{n^p} is a pp-series, then it converges if and only if p>1p>1.

Proof. We first consider the special case that p=1p = 1. This series ∑n=1∞1n\sum_{n=1}^\infty \frac{1}{n} is called the Harmonic series. By the integral test ∫1∞1xdxlim⁡t→∞∫1t1xdx=lim⁡t→∞ln⁡x|1t=∞\int_1^\infty \frac{1}{x} dx\lim_{t\to \infty} \int_1^t \frac{1}{x}dx = \lim_{t\to \infty} \ln x|_1^t = \infty. This diverges and hence, the harmonic series diverges.

Now, consider the case p≠1p\neq 1: ∫1∞1xpdx=lim⁡t→∞[x1−p1−p]1t=11−plimt→∞1tp−1−1\int_1^\infty \frac{1}{x^p}dx = \lim{t\to \infty} \left[\frac{x^{1-p}}{1-p}\right]_1^t = \frac{1}{1-p}\lim_{t\to \infty} \frac{1}{t^{p-1}} -1 which diverges if p−1<0(p<1)p-1<0 \, (p<1) and converges if p−1>0(p>1)p-1>0\, (p>1). ◻

9.5 Comparison test

Theorem 12 (Comparison test). Let ∑n=1∞an,∑n=1∞bn\sum_{n=1}^\infty a_n, \sum_{n=1}^\infty b_n be two series with 0≤an≤bn0\leq a_n \leq b_n. Then

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

  2. ∑n=1∞bn\sum_{n=1}^\infty b_n diverges if ∑n=1∞an\sum_{n=1}^\infty a_n diverges.

Proof. Let AnA_n and BnB_n represent the nthn^{th} partial sums of ∑n=1∞an\sum_{n=1}^\infty a_n and ∑n=1∞bn\sum_{n=1}^\infty b_n respectively. Suppose that Bn→LB_n\to L. Then since 0≤an≤bn0\leq a_n\leq b_n we have 0≤An≤Bn0\leq A_n\leq B_n for all n>0n>0. Now, AnA_n and BnB_n are both monotone increasing sequences and with Bn→LB_n\to L we have AnA_n is bounded above by LL. By monotone sequence theorem, AnA_n converges.

For the second part, AnA_n is monotone increasing to infinity. Thus, also Bn≥AnB_n\geq A_n is also increasing to infinity. ◻

9.6 Limit comparison test

Theorem 13 (Limit comparison test). Suppose there are two series ∑n=1∞an,∑n=1∞bn\sum_{n=1}^\infty a_n, \sum_{n=1}^\infty b_n with both an,bn>0a_n, b_n>0 for all nn. Then

  1. If limn→∞anbn=L≠0, or ∞\lim_{n\to \infty} \frac{a_n}{b_n} = L\neq 0,\text{ or } \infty then either both converge or both diverge.

  2. If limn→∞anbn=0\lim_{n\to \infty} \frac{a_n}{b_n} = 0 and ∑bn\sum b_n converges, then so does ∑an\sum a_n.

  3. If limn→∞anbn=∞\lim_{n\to \infty} \frac{a_n}{b_n} = \infty and ∑bn\sum b_n diverges, then so does ∑an\sum a_n.

Corollary 1. If ∑n=1∞|an|\sum_{n = 1}^\infty |a_n| converges then so does ∑n=1∞an\sum_{n=1}^\infty a_n.

Proof. Suppose that ∑n=1∞|an|\sum_{n = 1}^\infty |a_n| converges to MM. We have the inequality 0≤an+|an|≤2|an|.0\leq a_n +|a_n| \leq 2|a_n|. By the comparison test, then ∑n=1∞(an+|an|)\sum_{n=1}^\infty (a_n + |a_n|) converges (since ∑2|an|=2∑|an|=2M\sum 2|a_n| = 2\sum |a_n|= 2M). Assuming that ∑(an+|an|)=L\sum(a_n + |a_n|) = L then ∑an=L−M\sum a_n = L-M as required. ◻

Definition 4. If ∑an\sum a_n is a series such that ∑|an|\sum |a_n| converges, we say that ∑an\sum a_n is absolutely convergent.

If ∑an\sum a_n converges, but ∑|an|\sum |a_n| does not, then ∑an\sum a_n is said to be conditionally convergent.

Any series of the form ∑n(−1)ncn\sum_n (-1)^n c_n where cnc_n’s are positive, then the series is called an alternating series.

Theorem 14 (Alternating series test). Let ∑1∞(−1)n−1cn\sum_{1}^\infty (-1)^{n-1}c_n be an alternating series. If cn+1≤cnc_{n+1}\leq c_n for all n>0n>0 and lim⁡n→∞cn=0\lim_{n\to \infty} c_n = 0 then the series converges.

Proof. Supposing that lim⁡n→∞cn=0\lim_{n\to \infty} c_n = 0 and 0≤cn+1≤cn0\leq c_{n+1}\leq c_n, let SnS_n denote the partial sums of the series ∑n(−1)ncn\sum_n (-1)^n c_n. Note that S2nS_{2n} is monotone increasing and bounded above by c1c_1. So it remains to show that the limit of S2nS_{2n} is the same as the sum of the series. Note that S2n+1=S2n+c2n+1→S+0=SS_{2n+1} = S_{2n} + c_{2n+1}\to S + 0 = S so thus, the series converges. ◻

9.7 Alternating series estimation

Theorem 15 (Alternating series estimation theorem). If S=∑n=1∞(−1)n−1bnS = \sum_{n=1}^\infty(-1)^{n-1}b_n is the sum of an alternating series which satisfies 0≤bn+1≤bn and limn→∞bn=00 \leq b_{n+1}\leq b_n \text{ and } \lim_{n\to \infty} b_n = 0 then, Rn≤|S−S−n|≤bn+1.R_n \leq |S- S-n| \leq b_{n+1}.

Proof. We know from above that SS lies between two consecutive partial sums SnS_n and Sn+1S_{n+1}. It follows that |S−Sn|≤|Sn+1−Sn|=bn+1|S-S_n| \leq |S_{n+1} - S_n| = b_{n+1}. ◻

Note; the rule that the error is smaller than the first neglected term is valid only for alternating series.

9.8 Ratio test

Let ρ=lim⁡n→∞|an+1an|\rho = \lim_{n\to \infty} \left|\frac{a_{n+1}}{a_n}\right| for a series ∑nan\sum_n a_n. Then

if ρ<1\rho<1, the series is absolutely convergent and hence convergent

if ρ>1\rho >1 or =∞= \infty then the series is divergent

if ρ=1\rho = 1 or does not exist then the test is inconclusive.

9.9 Root test

Let ∑nan\sum_n a_n be a series. Then

if lim⁡n→∞|an|n<1\lim_{n\to \infty} \sqrt[n]{|a_n|} <1 then ∑an\sum a_n is absolutely convergent,

if lim⁡n→∞|an|n>1\lim_{n\to \infty} \sqrt[n]{|a_n|} >1 or =∞= \infty the series is divergent

and otherwise, if lim⁡n→∞|an|n=1\lim_{n\to \infty} \sqrt[n]{|a_n|} = 1 the test is inconcolsive

10 Series testing strategies

The following is a recipe for testing convergence of series.

  1. Check if ∑an\sum a_n is geometric, harmonic, p-series or telescoping

  2. Is the lim⁡n→∞an=0\lim_{n\to \infty} a_n = 0? If not, then the series diverges (by divergence test). Otherwise, convergence is still unknown

  3. Does |ak||a_k| resemble rkr^k or 1kp\frac{1}{k^p} for large kk? If so, try the comparison test, or limit comparison test with geometric series or a pp-series

  4. If ak=f(k)a_k = f(k) for some positive, decreasing continuous function ff, try the integral test

  5. If there are powers of nn or n!n! the ratio test is probably a good idea.

    • This test may result in the series diverges with ρ>1\rho>1 or =∞= \infty so there would be no need to proceed with alternating series.

    • This may show that ∑nan\sum_n a_n converges absolutely (when ρ<1\rho<1) hence converges

    • if ρ=1\rho =1 or doesn’t exist, this test has failed and says nothing

  6. Try the Root test, especially if you see powers of nn!

    • If ρ>1\rho>1 or =∞= \infty series diverges

    • if ρ<1\rho <1 it converges absolutely and hence converges

    • if ρ=1\rho = 1, or does not exist the try something else because we still don’t know

  7. if both ratio and root test have already failed, or it is clear that ∑|an|\sum|a_n| is divergent, try (if series is alternating) the alternating series test incase it is conditionally convergent.

  8. Error bounds:

    • if series converges by the integral test, use the integral formula for approximate value of series.

    • if the series converges by the alternating series test, use the alternating series estimation theorem to approximate the value.

11 Power series

A power series centered at aa is a series of the form ∑n=0∞cn(x−a)n\sum_{n=0}^\infty c_n (x-a)^n with xx a variable. This series differs in values because of the variable xx. This means that certain values cause series to converge and some won’t. This should give the impression that a power series is a function whose domain is a collection of values xx for which the series converges. When studying these, we will be interested in finding an elementary function ff such that f(x)=∑n=0∞cn(x−a)nf(x) = \sum _{n=0}^\infty c_n(x-a)^n as well as determining its domain.

Observations: We already know that ∑n=0∞rn=1+r+r2+…\sum_{n=0}^\infty r^n = 1 + r + r^2 + \dots converges to 11−r\frac{1}{1-r} for |r|<1|r|<1 while it diverges everywhere else. So, we could say that ∑n≥0xn\sum_{n\geq 0} x^n, centered at zero converges to the function 11−x\frac{1}{1-x} on the interval (−1,1)(-1, 1) and diverges elsewhere.

The function Tn(x):=∑k=0ncn(x−a)kT_n(x):= \sum_{k=0}^n c_n(x-a)^k is a polynomial. Recall, from Taylor polynomials that if T1(x)=1,T2(x)=1+x,…,Tk(x)=1+x+x2+…+xkT_1(x) = 1, T_2(x) = 1 + x, \dots, T_k(x) = 1 + x+ x^2 + \dots + x^k that lim⁡n→∞Tn(x)=11−x\lim_{n\to \infty} T_n(x) = \frac{1}{1-x}. Thus, a power series can be viewed as a function whose curve is a limit of a sequence of polynomials.

Also notice that a power series ∑ncn(x−a)n\sum_nc_n(x-a)^n always converges for x=ax = a.

Here, we will mainly discuss two things;

  1. For what values of xx does a power series converge? (this is called the radius and interval of convergence

  2. To what function, if any, does it converge to?

Theorem 16. The power series ∑k=0∞ck(x−a)k\sum_{k=0}^\infty c_k (x-a)^k converges either for x=ax = a, for all xx or there is a positive number RR such that the series converges for all |x−a|<R|x-a|<R and diverges for all |x−a|>R|x-a|>R.

Note: When a power series is known to converge for all |x−a|<R|x-a|<R, one must manually determine convergence at the endpoints of this open interval.

Proof. Given the power series ∑k=0∞ck(x−a)k\sum_{k=0}^\infty c_k (x-a)^k, suppose we define ρ=lim⁡n→∞|cn+1cn|\rho = \lim_{n\to \infty} \left|\frac{c_{n+1}}{c_n}\right|. Applying the ratio test to lim⁡n→∞|cn+1(x−a)n+1cn(x−a)n|=ρ|x−a|\lim_{n\to \infty} \left|\frac{c_{n+1}(x-a)^{n+1}}{c_n(x-a)^n}\right| = \rho |x-a|. Then this converges for ρ|x−a|<1\rho|x-a|<1 or, equivalently, |x−a|<1/ρ|x-a|<1/\rho. So to say that R=1/ρR = 1/\rho. ◻

Remark 2. The above theorem states convergence on intervals centered at aa. This is called the interval of convergence. Series may or may not converge at the endpoints of this interval. The R=1/ρ=lim⁡n→∞|cn+1cn|R = 1/\rho = \lim_{n\to \infty} \left|\frac{c_{n+1}}{c_n}\right|. If the power series converges to a function, we say f(x)=∑k=0∞ck(x−a)kf(x)=\sum_{k=0}^\infty c_k (x-a)^k for all |x−a|<R|x-a|<R

Example 38. Discuss the convergence of the following power series

  1. ∑n=1∞(−1)nn4n(x−2)n\sum_{n=1}^\infty \frac{(-1)^n}{n4^n}(x-2)^n Solution: Here R=1/ρ=limn→∞|(−1)nn4n(n+1)4n+1(−1)n+1|=limn→∞|4+4/n|=4R =1/\rho = \lim_{n\to \infty} \left|\frac{(-1)^n}{n4^n}\frac{(n+1)4^{n+1}}{(-1)^{n+1}}\right| = \lim_{n\to \infty}\left| 4 + 4/n\right| = 4 so |x−2|<4|x-2|<4 or −2<x<6-2<x<6. At the endpoints; when x=−2x = -2 this is ∑n=1∞(−1)n(−4)nn4n=∑n=1∞1n\sum_{n=1}^\infty \frac{(-1)^n(-4)^n}{n4^n} = \sum_{n=1}^\infty \frac{1}{n} when x=6x = 6 this becomes ∑n=1∞(−1)nn\sum_{n=1}^\infty \frac{(-1)^n} {n} which is known to converge! Thus, the interval of convergence is (−2,6](-2, 6].

  2. ∑n=1∞2nn!xn\sum_{n=1}^\infty \frac{2^n}{n!}x^n Solution: Here we find ρ=lim⁡n→∞|2n+1(n+1)!n!2n|=lim⁡n→∞2n+1=0\rho = \lim_{n\to \infty} \left|\frac{2^{n+1}}{(n+1)!}\frac{n!}{2^n}\right| = \lim_{n\to \infty} \frac{2}{n+1} = 0 hence 1/ρ=∞1/\rho = \infty which implies radius of convergence is infinite and series converges for all values of xx.

11.1 Functions as power series

Using that 11−x=∑k≥0xk\frac{1}{1-x} = \sum_{k\geq 0} x^k as a basis, we can find other functions expressed as power series!

For example,

  1. 13+x=1311−(−x3)=13∑n=0∞(−x3)n=∑n=0∞(−1)nxn3n+1\frac{1}{3+x} = \frac{1}{3} \frac{1}{1 - (-\frac{x}{3})} = \frac{1}{3}\sum_{n=0}^\infty \left(\frac{-x}{3}\right)^n = \sum_{n=0}^\infty \frac{(-1)^n x^n }{3^{n+1}} and the interval of convergence is |x3|<1\left|\frac{x}{3}\right|<1 or, |x|<3|x|<3.

  2. 11+x2=11−(−x2)=∑n=0∞(−1)nx2n\frac{1}{1+x^2} = \frac{1}{1-(-x^2)} = \sum_{n=0}^\infty (-1)^n x^2n with interval of convergence x2<1x^2<1 which is really just |x|<1|x|<1.

  3. x53+x2=x5311−(−x23)=x53∑n=0∞(−1)nx2n3n=∑n=0∞(−1)nx2n+53n+1\frac{x^5}{3 + x^2} = \frac{x^5}{3} \frac{1}{1- (-\frac{x^2}{3})} = \frac{x^5}{3}\sum_{n=0}^\infty \frac{(-1)^n x^2n}{3^n} = \sum_{n=0}^\infty \frac{(-1)^n x^{2n+5}}{3^{n+1}} with radius of convergence |x23|<1\left|\frac{x^2}{3}\right|<1 or |x|<3\left|x\right|<\sqrt{3}

Now that we can deal with everything of this form, we will need a new style.

Theorem 17. Suppose ∑n=0∞cn(x−a)n\sum_{n=0}^\infty c_n (x-a)^n has radius of convergence R>0R>0 and suppose that f(x)=∑n=0∞cn(x−a)nf(x) = \sum_{n=0}^\infty c_n (x-a)^n. Then f(x)f(x) is differentiable of |x−a|<R|x-a|<R and f′(x)=∑n=1∞ncn(x−a)n−1f\prime(x) = \sum_{n=1}^\infty nc_n(x-a)^{n-1} ∫axf(x)dx=∫ax∑n=0∞cn(x−a)ndx=∑n=0∞∫axcn(x−a)ndx=∑n=0∞cnxn+1n+1\int_a^x f(x)dx = \int_a^x \sum_{n=0}^\infty c_n (x-a)^n dx = \sum_{n=0}^\infty \int_a^x c_n (x-a)^n dx = \sum_{n=0}^\infty \frac{c_nx^{n+1}}{n+1} and both of these resulting power series have RR for their radius of convergence.

Example 39. Show that 1(1−x)2=∑n=0∞(n+1)xn\frac{1}{(1-x)^2} = \sum_{n=0}^\infty (n+1)x^n with R=1R= 1.

Solution: ddx(1−x)−1=1(1−x)2=ddx∑n=0∞xn=∑n=1∞nxn−1=∑n=0∞(n+1)xn\begin{align*} \frac{d}{dx} (1-x)^{-1} & = \frac{1}{(1-x)^2}\\& = \frac{d}{dx} \sum_{n=0}^\infty x^n\\ & = \sum_{n=1}^\infty nx^{n-1}\\ & = \sum_{n=0}^\infty (n+1)x^n \end{align*}

ln⁡(1+x)=∫ax11+tdt=∫ax11−(−t)dt=∫0x∑n=0∞(−1)ntndt=∑n=0∞(−1)n∫0xtndt=∑n=0∞(−1)nxn+1n+1=∑n=1∞(−1)n−1xnn\begin{align*} \ln (1+x) & = \int_a^x \frac{1}{1+t}dt \\ &= \int_a^x \frac{1}{1-(-t)} dt \\ &= \int_0^x \sum_{n=0}^\infty(-1)^n t^n 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}\\ &= \sum_{n=1}^\infty \frac{(-1)^{n-1}x^n}{n} \end{align*} and radius of convergence R=1R = 1.

arctan⁡x=∫0x11+x2dx=∫0x11−(−x2)dx=∫0x∑n=0∞(−1)nx2ndx=∑n=0∞(−1)nx2n+12n+1\begin{align*} \arctan x &= \int_0^x \frac{1}{1+x^2}dx \\ &= \int_0^x \frac{1}{1-(-x^2)}dx \\ &= \int_0^x \sum_{n=0}^\infty (-1)^n x^{2n}dx \\ &= \sum_{n=0}^\infty \frac{(-1)^n x^{2n+1}}{2n+1} \end{align*} for |x|<1|x| <1.

11.2 Taylor and Mclaurin series

Suppose f(x)f(x) has power series representation f(x)=∑n=0∞cn(x−a)nf(x)= \sum_{n=0}^\infty c_n(x-a)^n. What do the cnc_n’s look like?

Theorem 18. Let f(x)=∑n=0∞cn(x−a)nf(x)= \sum_{n=0}^\infty c_n(x-a)^n on |x−a|<R|x-a|<R, then cn=f(n)(a)n!\boxed{c_n = \frac{f^{(n)}(a)}{n!}} That is to say f(x)=∑n=0∞f(n)(a)n!(x−a)n.f(x)= \sum_{n=0}^\infty \frac{f^{(n)}(a)}{n!} (x-a)^n.

Example 40. We know that arctan⁡x=∑n=0∞(−1)nx2n+12n+1\arctan x = \sum_{n=0}^\infty \frac{(-1)^n x^{2n+1}}{2n+1} which implies that (−1)n2n+1=arctan⁡(n)(0)n!\frac{(-1)^n}{2n+1} = \frac{\arctan^{(n)}(0)}{n!} so the nthn^{th} derivative of arctan\arctan evaluated at zero is (−1)nn!2n+1\frac{(-1)^n n!}{2n+1}.

Definition 5 (Taylor series). Let f(x)f(x) be a function which is differentiable infinitely many times, then the series Tf,a(x)=∑n=0∞f(n)(a)n!(x−a)nT_{f, a}(x)= \sum_{n=0}^\infty \frac{f^{(n)}(a)}{n!}(x-a)^n is called the Taylor series generated by ff centred at aa.

Any Taylor series centred at 0, is called a McLaurin series.

Example 41.

  1. ∑n=0∞xn\sum_{n=0}^\infty x^n is the Mclaurin series for 11−x\frac{1}{1-x}.

  2. Find the McLaurin series generated by f(x)=exf(x)= e^x and determine the interval of convergence.

    Solution: We need only determine cn=f(n)(0)n!=exn!|x=0=1n!c_n = \frac{f^{(n)}(0)}{n!} = \frac{e^x}{n!}|_{x=0} = \frac{1}{n!}. So ex=∑n=0∞xnn!.e^x = \sum_{n=0}^\infty \frac{x^n}{n!}.

Notice that there exists functions which generate taylor and McLaurin series that do not converge to the original function. For example, the piecewise defined function f(x)={e−1/x2,x≠00,x=0f(x)= \begin{cases} e^{-1/x^2}, x\neq 0 \\ 0, x = 0 \end{cases} has a McLaurin series of 0, but this function is not the zero function.

The nthn^{th} degree taylor polynomial for ff, centred at aa is defined as the truncated version of its Taylor series Tn(x)=∑k=0nf(n)(a)n!(x−a)nT_n(x) = \sum_{k=0}^n \frac{f^{(n)}(a)}{n!}(x-a)^n. These are the partial sums of the Taylor series and again we can define the nthn^{th} remainder Rn(x)=Tf,a(x)−Tn(x)R_n(x) = T_{f, a}(x) - T_n(x).

We have that Rn(x)→0⇔Tn(x)→f(x)R_n(x) \to 0 \Leftrightarrow T_n(x) \to f(x)

To show that Rn(x)→0R_n(x)\to 0, we will use a tool called Taylor’s inequality.

Theorem 19. Let ∑n=0∞f(n)(a)n!(x−a)n\sum_{n=0}^\infty \frac{f^{(n)}(a)}{n!}(x-a)^n be a Taylor series with radius of convergence RR. Then |Rn(x)||R_n(x) | can be bounded above in the following way:

If |f(n+1)(x)|≤Mn|f^{(n+1)}(x)|\leq M_n on |x−a|<R|x - a|<R, then |Rn(x)|≤Mn|x−a|n+1(n+1)!, on |x−a|≤d<R.|R_n(x)| \leq \frac{M_n|x-a|^{n+1}}{(n+1)!}, \text{ on } |x-a|\leq d<R. If we can show that lim⁡n→∞Mn|x−a|n+1(n+1)!=0\lim_{n\to \infty}\frac{M_n|x-a|^{n+1}}{(n+1)!} =0 for all |x−a|≤d|x-a|\leq d, then f(x)=∑n=0∞f(n)(a)n!(x−a)nf(x)= \sum_{n=0}^\infty \frac{f^{(n)}(a)}{n!}(x-a)^n

Example 42. Recall, Mclaurin series of ex=∑n=0∞xnn!e^x = \sum_{n=0}^\infty \frac{x^n}{n!} has infinite radius of convergence
(since lim⁡n→∞xnn!=0\lim_{n\to \infty} \frac{x^n}{n!} = 0 since ∑n=0∞xnn!\sum_{n=0}^\infty \frac{x^n}{n!} converges by divergence test).

Show that ∑n=0∞xnn!\sum_{n=0}^\infty \frac{x^n}{n!} converges to exe^x.

Solution: Consider any interval [−k,k][-k,k]. Since exe^x is increasing let Mn=ekM_n = e^k. Then Taylors inequality guarantees that |Rn(x)|≤ek|x|n+1(n+1)!|R_n(x)|\leq \frac{e^k|x|^{n+1}}{(n+1)!}. Now, limn→∞|Rn(x)|≤eklimn→∞|x|n+1(n+1)!=0\lim_{n\to \infty} |R_n(x)| \leq e^k \lim_{n\to \infty}\frac{|x|^{n+1}}{(n+1)!} = 0 as required.

Example 43. Find the McLaurin series generated by sin⁡x\sin x.

Solution: since the derivatives of sine are cos⁡,−sin⁡,−cos⁡,sin⁡,…\cos, -\sin, -\cos, \sin, \dots and repeat every four, we find the values of these derivates to be 0,1,0,−1,…0, 1, 0, -1, \dots and repeat every four. Hence, then the series is given by 0+1⋅x+0x22!−1x33!+0x44!+…=x−x33!+x55!−x77!+…=∑k=0∞(−1)kx2k+1(2k+1)!0 + 1\cdot x + 0 \frac{x^2}{2!} - 1 \frac{x^3}{3!} + 0 \frac{x^4}{4!} + \dots = x - \frac{x^3}{3!} + \frac{x^5}{5!} - \frac{x^7}{7!} + \dots = \sum_{k=0}^\infty \frac{(-1)^k x^{2k+1} }{(2k+1)!} and R=limn→∞|(2n+3)!(2n+1)!|=limn→∞(2n+3)(2n+2)=∞R = \lim_{n\to \infty} \left|\frac{(2n+3)!}{(2n+1)!}\right| = \lim_{n\to \infty} (2n+3)(2n+2) = \infty

Does the series generated by sin⁡x\sin x converge to sin⁡x\sin x?

We have ∑n=0∞sin⁡(n)(0)n!(x−0)n=∑n=0∞(−1)nx2n+1(2n+1)!\sum_{n=0}^\infty\frac{\sin^{(n)}(0)}{n!}(x-0)^n = \sum_{n=0}^\infty \frac{(-1)^nx^{2n+1}}{(2n+1)!} and |sin⁡(n)(x)≤1=Mn|\sin^{( n)}(x) \leq 1 = M_n for all x∈[−k,k]x\in [-k,k]. Thus, |Rn(x)|≤|x|n+1(n+1)!→0|R_n(x) | \leq \frac{|x|^{n+1}}{(n+1)!} \to 0 So the Taylor series generated by sin⁡x\sin x converges to sin⁡x\sin x for all xx.

Note that if you wanted to approximate sin⁡x\sin x near x=50x= 50, choose a=50a = 50.

Example 44. Estimate sin⁡(0.1)\sin(0.1) with error <10−8<10^{-8}.

Solution: Recall sin⁡x=∑n=0∞(−1)nx2n+1(2n+1)!\sin x = \sum_{n=0}^\infty \frac{(-1)^nx^{2n+1}}{(2n+1)!} and we know that |Rn(x)|≤|x|n+1(n+1)!|R_n(x)| \leq \frac{|x|^{n+1}}{(n+1)!}. That is, |sin⁡x−Tn(x)|≤|x|n+1(n+1)!<10−8|0.1|n+1(n+1)!<10−8\begin{align*} |\sin x - T_n(x) | \leq& \frac{|x|^{n+1}}{(n+1)!}<10^{-8}\\ &\frac{|0.1|^{n+1}}{(n+1)!}<10^{-8}\\ \end{align*} Try n=6n=6, and find that R6(0.1)≤(0.1)7(6+1)!=1.9×10−11<10−8R_6(0.1) \leq \frac{(0.1)^{7}}{(6+1)!} = 1.9\times 10^{-11}<10^{-8}. Thus, T6(0.1)=T5(0.1)=(0.1)−(0.1)33!+(0.1)55!=0.099833T_6(0.1) = T_5(0.1) = (0.1) - \frac{(0.1)^3}{3!} + \frac{(0.1)^5}{5!} = 0.099833.

Example 45. Find the McLaurin series for cos⁡x\cos x.

Solution: cos⁡x=ddxsin⁡x=ddx∑n=0∞(−1)nx2n+1(2n+1)!=∑n=0∞(−1)nx2n(2n)!\cos x = \frac{d}{dx}\sin x = \frac{d}{dx} \sum_{n=0}^\infty \frac{(-1)^n x^{2n+1}}{(2n+1)!} = \sum_{n=0}^\infty \frac{(-1)^n x^{2n}}{(2n)!}

Theorem 20. Let ∑nanxn,∑nbnxn\sum_n a_n x^n, \sum_n b_nx^n be two McLaurin series with radii of convergence RaR_a and RbR_b respectively. Then ∑ncnxn=(∑nanxn)⋅(∑nbnxn)\sum_n c_n x^n = \left(\sum_n a_n x^n\right)\cdot \left(\sum_n b_n x^n\right) where cn=a0bn+a1bn−1+…+an−1b1+anb0=∑i=0naibn−ic_n = a_0b_n + a_1b_{n-1} +\dots +a_{n-1}b_1 + a_n b_0 = \sum_{i =0}^n a_ib_{n-i} has interval of convergence R=min⁡{Ra,Rb}R = \min\{R_a, R_b\}.

Example 46. Find the Mclaurin series for 1x−1ln⁡(1−x)\frac{1}{x-1}\ln(1-x).

Solution: 1x−1=−11−x=(−1)(1+x+x2+…)\frac{1}{x-1} = \frac{-1}{1-x} = (-1)(1+x + x^2 + \dots ) ln⁡(1−x)=−x−x22−x33−x44−…\ln(1-x) = - x - \frac{x^2}{2} - \frac{x^3}{3}- \frac{x^4}{4} - \dots which implies 1x−1ln⁡(1−x)=(1+x+x2+…)(x+x22+x33+x44+…)=1(0)+(1(0)+(1)(1))x+(1(0)+1(12)+1(1))x2+(1+1/2+1/3)x3+…=∑n=0∞(1+1/2+1/3+…+1/n)xn\begin{align*} \frac{1}{x-1}\ln(1-x) &= (1+x + x^2 + \dots )(x + \frac{x^2}{2} + \frac{x^3}{3}+\frac{x^4}{4} + \dots )\\ &= 1(0) + \left(1(0) + (1)(1)\right)x + \left(1(0) + 1(\frac{1}{2}) + 1(1)\right)x^2 + \left(1 + 1/2 + 1/3\right)x^3 + \dots \\ &= \sum_{n=0}^\infty \left(1 + 1/2 + 1/3 + \dots +1/n \right)x^n \end{align*} and R=1R = 1.

Everyone should know the following list of Taylor expansions

ex=∑n≥0xnn!cos⁡x=∑n≥0(−1)nx2n(2n)!sin⁡x=∑n≥0(−1)nx2n+1(2n+1)!arctan⁡x=∑n≥0(−1)nx2n+12n+111−x=∑n≥0xnln⁡(1−x)=−∑n≥0xnn\begin{align*} e^x &= \sum_{n\geq 0}\frac{x^n}{n!}\\ \cos x &= \sum_{n\geq 0}\frac{(-1)^nx^{2n}}{(2n)!}\\ \sin x &= \sum_{n\geq 0}\frac{(-1)^nx^{2n+1}}{(2n+1)!}\\ \arctan x &= \sum_{n\geq 0}\frac{(-1)^nx^{2n+1}}{2n+1}\\ \frac{1}{1-x} &= \sum_{n\geq 0 } x^n\\ \ln (1-x) & = - \sum_{n\geq 0 } \frac{x^n}{n}\\ \end{align*}

12 Applications of Taylor and McLaurin series

  1. Find the sum of the series 1−π22!+π44!−π66!+…=∑k≥0(−1)kπ2k(2k)!=cos⁡(π)=−11 - \frac{\pi^2}{2!} + \frac{\pi^4}{4!} - \frac{\pi^6}{6!} + \dots = \sum_{k\geq 0} \frac{(-1)^k\pi^{2k}}{(2k)!} = \cos (\pi) = -1.

  2. Approximate the integral ∫011−cos⁡xx2dx\int_0^1 \frac{1- \cos x}{x^2} dx with error less than 0.000010.00001.

    Solution: ∫011−cos⁡xx2dx=∫011x2(1−(1−x2/2!+x4/4!−x6/6!+…)dx=∫011x2(x2/2!−x4/4!+x6/6!+…)dx=∫01(1/2!−x2/4!+x4/6!+…)dx=[x2−x33⋅4!+x55⋅6!+…]01=12!−13⋅4!+15⋅6!−17⋅8!+…\begin{align*} \int_0^1 \frac{1- \cos x}{x^2} dx&= \int_0^1 \frac{1}{x^2} \left(1 - (1 - x^2/2! + x^4/4!- x^6/6! + \dots\right)dx\\ &= \int_0^1\frac{1}{x^2}\left(x^2/2! - x^4/4!+ x^6/6! + \dots\right)dx\\ &= \int_0^1\left(1/2! - x^2/4!+ x^4/6! + \dots\right)dx\\ &= \left[\frac{x}{2} - \frac{x^3}{3\cdot 4!} + \frac{x^5}{5\cdot 6!} + \dots \right]_0^1\\ &= \frac{1}{2!} - \frac{1}{3\cdot 4!}+\frac{1}{5\cdot 6!}-\frac{1}{7\cdot 8!} + \dots \end{align*} This is an alternating series, so the error bound for SnS_n is cn+1c_{n+1}. Letting n=4n= 4, then c4=17⋅8!=0.0000036<0.00001c_4 = \frac{1}{7\cdot 8! } = 0.0000036<0.00001. Therefor S3S_3 is appropriate and S3=12!−13⋅4!+15⋅6!≈0.486388S_3 = \frac{1}{2!} - \frac{1}{3\cdot 4!}+\frac{1}{5\cdot 6!} \approx 0.486388

  3. Approximate the integral ∫011−cos⁡xx2dx\int_0^1 \frac{1- \cos x}{x^2} dx with error less than 10−710^{-7}.

    Solution:

    |sinx−(x−x33!+x55!+)|≤|Rn(x)|\begin{align*} \left|\sin x - \left(x - \frac{x^3}{3!} + \frac{x^5}{5!} + \right)\right| \leq \left|R_n(x)\right| \end{align*} implies |sin⁡xx−(1x)(x−x33!+x55!+)|≤|Rn(x)x|\left|\frac{\sin x}{x} - \left(\frac{1}{x}\right)\left(x - \frac{x^3}{3!} + \frac{x^5}{5!} + \right)\right| \leq \left|\frac{R_n(x)}{x}\right| so |∫01/2sin⁡xxdx−∫01/2(1x)(x−x33!+x55!+)dx|≤∫01/2|Rn(x)x|dx≤∫01/21xxn+1(n+1)!dx≤∫01/2xn(n+1)!dx=[xn+1(n+1)(n+1)!]01/2=12n+1(n+1)(n+1)!\begin{align*} \left|\int_0^{1/2}\frac{\sin x}{x}dx - \int_0^{1/2}\left(\frac{1}{x}\right)\left(x - \frac{x^3}{3!} + \frac{x^5}{5!} + \right)dx\right| &\leq \int_0^{1/2} \left|\frac{R_n(x)}{x}\right|dx \\ & \leq \int_0^{1/2}\frac{1}{x} \frac{x^{n+1}}{(n+1)!} dx \\ &\leq \int_0^{1/2}\frac{x^n}{(n+1)!}dx\\ &= \left[\frac{x^{n+1}}{(n+1)(n+1)!}\right]_0^{1/2}\\ &= \frac{1}{2^{n+1}(n+1)(n+1)!} \end{align*}

    When n=6n=6, this is 127(7)7!\frac{1}{2^7(7)7!}.

12.1 Binomial series

Recall, if n>0n>0 that (a+b)n=∑k=0n(nk)akbn−k(a+b)^n = \sum_{k=0}^n {n\choose k} a^kb^{n-k} where (nk)=n!k!(n−k)!{n\choose k} = \frac{n! }{k!(n-k)!}.

Definition 6. For α\alpha and real number and kk a positive integer, define (αk){\alpha\choose k} as follows: (α0)=1,(αk)=α(α−1)(α−2)…(α−k+1)k!{\alpha\choose 0 } = 1, \quad {\alpha\choose k} = \frac{\alpha(\alpha-1)(\alpha-2)\dots (\alpha- k+1)}{k!}

Theorem 21 (Binomial Series Theorem). Let α∈ℝ\alpha\in \mathbb{R}. Then the McLaurin series for (1+x)α=∑k=0∞(αk)xk(1+x)^\alpha= \sum_{k=0}^\infty {\alpha\choose k} x^k with interval of convergence (−1,1)(-1, 1).

Example 47. Find a McLaurin series for 19−x\frac{1}{\sqrt{9-x}}.

Solution: 19−x=13(1+(−x/9))−1/2,let u=x/9=13(1+−1/21!(−u)+(−1/2)(−1/2−1)2!(−u)2+(−1/2)(−1/2−1)(−1/2−2)3!(−u)3+…)=13(1+12u+1⋅3222!u2+1⋅3⋅5233!u3+…+1⋅3⋅5⋯(2n−1)2nn!un+…)=13∑n=0∞1⋅3⋅5⋯(2n−1)2nn!un\begin{align*} \frac{1}{\sqrt{9-x}} & = \frac{1}{3}\left(1+ (-x/9)\right)^{-1/2}, \qquad \text{let } u = x/9\\ &= \frac{1}{3}\left(1 + \frac{-1/2}{1!}(-u) + \frac{(-1/2)(-1/2-1)}{2!}(-u)^2 + \frac{(-1/2)(-1/2-1)(-1/2-2)}{3!}(-u)^3 +\dots \right)\\ &= \frac{1}{3}\left(1 + \frac{1}{2}u + \frac{1\cdot 3}{2^22!}u^2 + \frac{1\cdot 3\cdot 5}{2^33!}u^3 +\dots + \frac{1\cdot 3 \cdot 5\cdots (2n-1)}{2^n n!}u^n+\dots \right)\\ &= \frac{1}{3} \sum_{n=0}^\infty \frac{1\cdot 3\cdot 5\cdots (2n-1)}{2^n n!}u^n \end{align*}

So, now the McLaurin series for f(x)=13∑n≥01⋅3⋅5⋯(2n−1)2nn!9nxnf(x)=\frac{1}{3} \sum_{n\geq 0} \frac{1\cdot 3\cdot 5\cdots (2n-1)}{2^n n!9^n}x^n we can compute f(12)(0)f^{(12)}(0) since we know the series! Indeed,

f(12)(0)12!=1⋅3⋅5⋯(2n−1)3⋅21212!9n⇒f(12)(0)=1⋅3⋅5⋯(2n−1)3⋅212⋅9n\frac{f^{(12)}(0)}{12!} = \frac{1\cdot 3\cdot 5\cdots (2n-1)}{3\cdot 2^{12}12! 9^n }\Rightarrow f^{(12)}(0) = \frac{1\cdot 3\cdot 5\cdots (2n-1)}{3\cdot 2^{12}\cdot 9^n }

12.2 One last application

The pendulum of length LL;

T=4Lg∫0π/211−k2sin⁡2ϕdϕT = 4\sqrt{\frac{L}{g}}\int_0^{\pi/2}\frac{1}{\sqrt{1- k^2\sin^2\phi}}d\phi We would like to approximate TT given ϕ0\phi_0

Express 11−k2sin⁡2ϕ=∑n=0∞1⋅3⋅5⋯(2n−1)2nn!(k2sin⁡2ϕ)n=∑n=0∞1⋅3⋅5⋯(2n−1)2nn!k2nsin⁡2nϕ\frac{1}{\sqrt{1- k^2\sin^2\phi}} = \sum_{n=0}^\infty \frac{1\cdot 3\cdot 5\cdots (2n-1)}{2^n n!}(k^2\sin^2\phi)^n =\sum_{n=0}^\infty \frac{1\cdot 3\cdot 5\cdots (2n-1)}{2^n n!}k^{2n}\sin^{2n}\phi

Then 4Lg∫0π/211−k2sin⁡2ϕdϕ=4Lg∫0π/2∑n=0∞1⋅3⋅5⋯(2n−1)2nn!k2nsin⁡2nϕdϕ4\sqrt{\frac{L}{g}}\int_0^{\pi/2}\frac{1}{\sqrt{1- k^2\sin^2\phi}}d\phi = 4\sqrt{\frac{L}{g}}\int_0^{\pi/2}\sum_{n=0}^\infty \frac{1\cdot 3\cdot 5\cdots (2n-1)}{2^n n!}k^{2n}\sin^{2n}\phi d\phi