Sequences
Definition
A sequence is an ordered list of numbers a 1 , a 2 , a 3 , … a_1, a_2, a_3, \ldots a 1 , a 2 , a 3 , … written { a n } n = 1 ∞ \{a_n\}_{n=1}^{\infty} { a n } n = 1 ∞
or simply { a n } \{a_n\} { a n } . Each a n a_n a n is called a term of the sequence. A series is the sum of
the terms of a sequence: ∑ n = 1 ∞ a n \displaystyle\sum_{n=1}^{\infty} a_n n = 1 ∑ ∞ a n .
A sequence converges to a limit L L L if lim n → ∞ a n = L \displaystyle\lim_{n \to \infty} a_n = L n → ∞ lim a n = L . Otherwise it
diverges .
Arithmetic Sequences
Definition
An arithmetic sequence has a constant common difference d d d between consecutive terms:
a n = a 1 + ( n − 1 ) d a_n = a_1 + (n - 1)d a n = a 1 + ( n − 1 ) d
where a 1 a_1 a 1 is the first term and d = a n + 1 − a n d = a_{n+1} - a_n d = a n + 1 − a n for all n n n .
Sum of an Arithmetic Sequence
The sum of the first n n n terms is:
S n = n 2 ( a 1 + a n ) = n 2 [ 2 a 1 + ( n − 1 ) d ] S_n = \frac{n}{2}(a_1 + a_n) = \frac{n}{2}\bigl[2a_1 + (n-1)d\bigr] S n = 2 n ( a 1 + a n ) = 2 n [ 2 a 1 + ( n − 1 ) d ]
Proof. Write the sum forward and backward:
S n = a 1 + ( a 1 + d ) + ( a 1 + 2 d ) + ⋯ + a n S_n = a_1 + (a_1 + d) + (a_1 + 2d) + \cdots + a_n S n = a 1 + ( a 1 + d ) + ( a 1 + 2 d ) + ⋯ + a n
S n = a n + ( a n − d ) + ( a n − 2 d ) + ⋯ + a 1 S_n = a_n + (a_n - d) + (a_n - 2d) + \cdots + a_1 S n = a n + ( a n − d ) + ( a n − 2 d ) + ⋯ + a 1
Adding: 2 S n = n ( a 1 + a n ) 2S_n = n(a_1 + a_n) 2 S n = n ( a 1 + a n ) , hence S n = n 2 ( a 1 + a n ) S_n = \dfrac{n}{2}(a_1 + a_n) S n = 2 n ( a 1 + a n ) .
Example. Find the sum of the first 50 positive odd numbers.
a 1 = 1 a_1 = 1 a 1 = 1 , d = 2 d = 2 d = 2 , a 50 = 1 + 49 ⋅ 2 = 99 a_{50} = 1 + 49 \cdot 2 = 99 a 50 = 1 + 49 ⋅ 2 = 99 .
S 50 = 50 2 ( 1 + 99 ) = 2500 S_{50} = \frac{50}{2}(1 + 99) = 2500 S 50 = 2 50 ( 1 + 99 ) = 2500
Arithmetic Mean
The arithmetic mean of a a a and b b b is a + b 2 \dfrac{a + b}{2} 2 a + b . In an arithmetic sequence, each term is
the arithmetic mean of its neighbours.
Geometric Sequences
Definition
A geometric sequence has a constant common ratio r r r between consecutive terms:
a n = a 1 ⋅ r n − 1 a_n = a_1 \cdot r^{n-1} a n = a 1 ⋅ r n − 1
where a 1 a_1 a 1 is the first term and r = a n + 1 a n r = \dfrac{a_{n+1}}{a_n} r = a n a n + 1 for all n n n .
Sum of a Finite Geometric Series
For r ≠ 1 r \ne 1 r = 1 :
S n = a 1 ( 1 − r n ) 1 − r = a 1 ( r n − 1 ) r − 1 S_n = \frac{a_1(1 - r^n)}{1 - r} = \frac{a_1(r^n - 1)}{r - 1} S n = 1 − r a 1 ( 1 − r n ) = r − 1 a 1 ( r n − 1 )
Proof. S n = a 1 + a 1 r + a 1 r 2 + ⋯ + a 1 r n − 1 S_n = a_1 + a_1 r + a_1 r^2 + \cdots + a_1 r^{n-1} S n = a 1 + a 1 r + a 1 r 2 + ⋯ + a 1 r n − 1 .
r S n = a 1 r + a 1 r 2 + ⋯ + a 1 r n − 1 + a 1 r n rS_n = a_1 r + a_1 r^2 + \cdots + a_1 r^{n-1} + a_1 r^n r S n = a 1 r + a 1 r 2 + ⋯ + a 1 r n − 1 + a 1 r n
Subtracting: S n − r S n = a 1 − a 1 r n S_n - rS_n = a_1 - a_1 r^n S n − r S n = a 1 − a 1 r n .
S n ( 1 − r ) = a 1 ( 1 − r n ) ⟹ S n = a 1 ( 1 − r n ) 1 − r S_n(1 - r) = a_1(1 - r^n) \implies S_n = \frac{a_1(1 - r^n)}{1 - r} S n ( 1 − r ) = a 1 ( 1 − r n ) ⟹ S n = 1 − r a 1 ( 1 − r n )
Sum of an Infinite Geometric Series
If ∣ r ∣ < 1 |r| \lt 1 ∣ r ∣ < 1 , the infinite geometric series converges:
S ∞ = ∑ n = 1 ∞ a 1 r n − 1 = a 1 1 − r S_{\infty} = \sum_{n=1}^{\infty} a_1 r^{n-1} = \frac{a_1}{1 - r} S ∞ = ∑ n = 1 ∞ a 1 r n − 1 = 1 − r a 1
If ∣ r ∣ ≥ 1 |r| \ge 1 ∣ r ∣ ≥ 1 , the series diverges.
Example. Express 0. 7 ‾ 0.\overline{7} 0. 7 as a fraction.
0. 7 ‾ = 7 10 + 7 100 + 7 1000 + ⋯ 0.\overline{7} = \frac{7}{10} + \frac{7}{100} + \frac{7}{1000} + \cdots 0. 7 = 10 7 + 100 7 + 1000 7 + ⋯
This is a geometric series with a 1 = 7 10 a_1 = \dfrac{7}{10} a 1 = 10 7 and r = 1 10 r = \dfrac{1}{10} r = 10 1 .
S ∞ = 7 / 10 1 − 1 / 10 = 7 / 10 9 / 10 = 7 9 S_{\infty} = \frac{7/10}{1 - 1/10} = \frac{7/10}{9/10} = \frac{7}{9} S ∞ = 1 − 1/10 7/10 = 9/10 7/10 = 9 7
Example. Evaluate ∑ n = 0 ∞ 3 4 n \displaystyle\sum_{n=0}^{\infty} \frac{3}{4^n} n = 0 ∑ ∞ 4 n 3 .
a 1 = 3 a_1 = 3 a 1 = 3 , r = 1 4 r = \dfrac{1}{4} r = 4 1 .
S ∞ = 3 1 − 1 / 4 = 3 3 / 4 = 4 S_{\infty} = \frac{3}{1 - 1/4} = \frac{3}{3/4} = 4 S ∞ = 1 − 1/4 3 = 3/4 3 = 4
Geometric Mean
The geometric mean of positive numbers a a a and b b b is a b \sqrt{ab} ab . In a geometric sequence with
positive terms, each term is the geometric mean of its neighbours.
Sigma Notation
Definition
∑ k = m n a k = a m + a m + 1 + ⋯ + a n \sum_{k=m}^{n} a_k = a_m + a_{m+1} + \cdots + a_n ∑ k = m n a k = a m + a m + 1 + ⋯ + a n
Properties
∑ k = m n c ⋅ a k = c ∑ k = m n a k \sum_{k=m}^{n} c \cdot a_k = c\sum_{k=m}^{n} a_k ∑ k = m n c ⋅ a k = c ∑ k = m n a k
∑ k = m n ( a k + b k ) = ∑ k = m n a k + ∑ k = m n b k \sum_{k=m}^{n}(a_k + b_k) = \sum_{k=m}^{n} a_k + \sum_{k=m}^{n} b_k ∑ k = m n ( a k + b k ) = ∑ k = m n a k + ∑ k = m n b k
Sum Closed Form ∑ k = 1 n k \displaystyle\sum_{k=1}^{n} k k = 1 ∑ n k n ( n + 1 ) 2 \dfrac{n(n+1)}{2} 2 n ( n + 1 ) ∑ k = 1 n k 2 \displaystyle\sum_{k=1}^{n} k^2 k = 1 ∑ n k 2 n ( n + 1 ) ( 2 n + 1 ) 6 \dfrac{n(n+1)(2n+1)}{6} 6 n ( n + 1 ) ( 2 n + 1 ) ∑ k = 1 n k 3 \displaystyle\sum_{k=1}^{n} k^3 k = 1 ∑ n k 3 n 2 ( n + 1 ) 2 4 \dfrac{n^2(n+1)^2}{4} 4 n 2 ( n + 1 ) 2 ∑ k = 0 n r k \displaystyle\sum_{k=0}^{n} r^k k = 0 ∑ n r k 1 − r n + 1 1 − r , r ≠ 1 \dfrac{1 - r^{n+1}}{1 - r}, \quad r \ne 1 1 − r 1 − r n + 1 , r = 1
Convergence Tests
The n n n -th Term Test (Divergence Test)
If lim n → ∞ a n ≠ 0 \displaystyle\lim_{n \to \infty} a_n \ne 0 n → ∞ lim a n = 0 , then ∑ a n \displaystyle\sum a_n ∑ a n diverges.
Caution. If lim n → ∞ a n = 0 \lim_{n \to \infty} a_n = 0 lim n → ∞ a n = 0 , the series may or may not converge.
The harmonic series ∑ 1 n \sum \dfrac{1}{n} ∑ n 1 diverges despite its terms tending to zero.
Comparison Test
If 0 ≤ a n ≤ b n 0 \le a_n \le b_n 0 ≤ a n ≤ b n for all n n n :
If ∑ b n \sum b_n ∑ b n converges, then ∑ a n \sum a_n ∑ a n converges.
If ∑ a n \sum a_n ∑ a n diverges, then ∑ b n \sum b_n ∑ b n diverges.
Ratio Test
For a series ∑ a n \sum a_n ∑ a n with a n ≠ 0 a_n \ne 0 a n = 0 :
L = lim n → ∞ ∣ a n + 1 a n ∣ L = \lim_{n \to \infty} \left|\frac{a_{n+1}}{a_n}\right| L = lim n → ∞ a n a n + 1
L < 1 L \lt 1 L < 1 : the series converges absolutely .
L > 1 L \gt 1 L > 1 : the series diverges .
L = 1 L = 1 L = 1 : the test is inconclusive .
Example. Does ∑ n = 1 ∞ n 2 2 n \displaystyle\sum_{n=1}^{\infty} \frac{n^2}{2^n} n = 1 ∑ ∞ 2 n n 2 converge?
L = lim n → ∞ ( n + 1 ) 2 / 2 n + 1 n 2 / 2 n = lim n → ∞ ( n + 1 ) 2 2 n 2 = 1 2 < 1 L = \lim_{n \to \infty} \frac{(n+1)^2 / 2^{n+1}}{n^2 / 2^n} = \lim_{n \to \infty} \frac{(n+1)^2}{2n^2} = \frac{1}{2} \lt 1 L = lim n → ∞ n 2 / 2 n ( n + 1 ) 2 / 2 n + 1 = lim n → ∞ 2 n 2 ( n + 1 ) 2 = 2 1 < 1
The series converges.
Integral Test
If f f f is continuous, positive, and decreasing on [ 1 , ∞ ) [1, \infty) [ 1 , ∞ ) , then ∑ f ( n ) \sum f(n) ∑ f ( n ) converges if and
only if ∫ 1 ∞ f ( x ) d x \displaystyle\int_1^{\infty} f(x)\,dx ∫ 1 ∞ f ( x ) d x converges.
Example. The harmonic series diverges because:
∫ 1 ∞ 1 x d x = lim b → ∞ ln b = ∞ \int_1^{\infty} \frac{1}{x}\,dx = \lim_{b \to \infty} \ln b = \infty ∫ 1 ∞ x 1 d x = lim b → ∞ ln b = ∞
Alternating Series Test (Leibniz Test)
An alternating series ∑ ( − 1 ) n + 1 a n \sum (-1)^{n+1} a_n ∑ ( − 1 ) n + 1 a n (or ∑ ( − 1 ) n a n \sum (-1)^n a_n ∑ ( − 1 ) n a n ) converges if:
a n a_n a n is decreasing: a n + 1 ≤ a n a_{n+1} \le a_n a n + 1 ≤ a n for all n n n .
lim n → ∞ a n = 0 \displaystyle\lim_{n \to \infty} a_n = 0 n → ∞ lim a n = 0 .
Example. ∑ n = 1 ∞ ( − 1 ) n + 1 n \displaystyle\sum_{n=1}^{\infty} \frac{(-1)^{n+1}}{n} n = 1 ∑ ∞ n ( − 1 ) n + 1 converges (the alternating harmonic
series) since 1 n \dfrac{1}{n} n 1 decreases to 0 0 0 .
The Binomial Theorem
Finite Binomial Expansion
For n ∈ ′ { ′ Z ′ } ′ + n \in \mathbb{'\{'}Z{'\}'}^+ n ∈ ′ { ′ Z ′ } ′ + :
( a + b ) n = ∑ k = 0 n ( n k ) a n − k b k (a + b)^n = \sum_{k=0}^{n} \binom{n}{k} a^{n-k} b^k ( a + b ) n = ∑ k = 0 n ( k n ) a n − k b k
where the binomial coefficient is:
( n k ) = n ! k ! ( n − k ) ! \binom{n}{k} = \frac{n!}{k!(n-k)!} ( k n ) = k ! ( n − k )! n !
General Binomial Expansion
For any n ∈ ′ { ′ R ′ } ′ n \in \mathbb{'\{'}R{'\}'} n ∈ ′ { ′ R ′ } ′ and ∣ x ∣ < 1 |x| \lt 1 ∣ x ∣ < 1 :
( 1 + x ) n = 1 + n x + n ( n − 1 ) 2 ! x 2 + n ( n − 1 ) ( n − 2 ) 3 ! x 3 + ⋯ (1 + x)^n = 1 + nx + \frac{n(n-1)}{2!}x^2 + \frac{n(n-1)(n-2)}{3!}x^3 + \cdots ( 1 + x ) n = 1 + n x + 2 ! n ( n − 1 ) x 2 + 3 ! n ( n − 1 ) ( n − 2 ) x 3 + ⋯
This is an infinite series that converges for ∣ x ∣ < 1 |x| \lt 1 ∣ x ∣ < 1 (and at the endpoints depending on n n n ).
Example. Expand ( 1 + x ) − 2 (1 + x)^{-2} ( 1 + x ) − 2 up to the term in x 3 x^3 x 3 .
( 1 + x ) − 2 = 1 + ( − 2 ) x + ( − 2 ) ( − 3 ) 2 x 2 + ( − 2 ) ( − 3 ) ( − 4 ) 6 x 3 + ⋯ (1 + x)^{-2} = 1 + (-2)x + \frac{(-2)(-3)}{2}x^2 + \frac{(-2)(-3)(-4)}{6}x^3 + \cdots ( 1 + x ) − 2 = 1 + ( − 2 ) x + 2 ( − 2 ) ( − 3 ) x 2 + 6 ( − 2 ) ( − 3 ) ( − 4 ) x 3 + ⋯
= 1 − 2 x + 3 x 2 − 4 x 3 + ⋯ = 1 - 2x + 3x^2 - 4x^3 + \cdots = 1 − 2 x + 3 x 2 − 4 x 3 + ⋯
Example. Find the coefficient of x 3 x^3 x 3 in the expansion of ( 2 − 3 x ) 1 / 2 (2 - 3x)^{1/2} ( 2 − 3 x ) 1/2 .
( 2 − 3 x ) 1 / 2 = 2 ( 1 − 3 x 2 ) 1 / 2 (2 - 3x)^{1/2} = \sqrt{2}\left(1 - \frac{3x}{2}\right)^{1/2} ( 2 − 3 x ) 1/2 = 2 ( 1 − 2 3 x ) 1/2
= 2 [ 1 + 1 2 ( − 3 x 2 ) + ( 1 / 2 ) ( − 1 / 2 ) 2 ( − 3 x 2 ) 2 + ( 1 / 2 ) ( − 1 / 2 ) ( − 3 / 2 ) 6 ( − 3 x 2 ) 3 + ⋯ ] = \sqrt{2}\left[1 + \frac{1}{2}\!\left(-\frac{3x}{2}\right) + \frac{(1/2)(-1/2)}{2}\!\left(-\frac{3x}{2}\right)^{\!2} + \frac{(1/2)(-1/2)(-3/2)}{6}\!\left(-\frac{3x}{2}\right)^{\!3} + \cdots\right] = 2 [ 1 + 2 1 ( − 2 3 x ) + 2 ( 1/2 ) ( − 1/2 ) ( − 2 3 x ) 2 + 6 ( 1/2 ) ( − 1/2 ) ( − 3/2 ) ( − 2 3 x ) 3 + ⋯ ]
The x 3 x^3 x 3 coefficient:
2 ⋅ − 3 / 8 6 ⋅ ( − 27 8 ) = 2 ⋅ 81 384 = 27 2 128 \sqrt{2} \cdot \frac{-3/8}{6} \cdot \left(-\frac{27}{8}\right) = \sqrt{2} \cdot \frac{81}{384} = \frac{27\sqrt{2}}{128} 2 ⋅ 6 − 3/8 ⋅ ( − 8 27 ) = 2 ⋅ 384 81 = 128 27 2
Maclaurin Series
Definition
The Maclaurin series of a function f f f is its Taylor series expansion about x = 0 x = 0 x = 0 :
f ( x ) = ∑ n = 0 ∞ f ( n ) ( 0 ) n ! x n = f ( 0 ) + f ′ ( 0 ) x + f ′ ′ ( 0 ) 2 ! x 2 + f ′ ′ ′ ( 0 ) 3 ! x 3 + ⋯ f(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(0)}{n!}\,x^n = f(0) + f'(0)x + \frac{f''(0)}{2!}x^2 + \frac{f'''(0)}{3!}x^3 + \cdots f ( x ) = ∑ n = 0 ∞ n ! f ( n ) ( 0 ) x n = f ( 0 ) + f ′ ( 0 ) x + 2 ! f ′′ ( 0 ) x 2 + 3 ! f ′′′ ( 0 ) x 3 + ⋯
Standard Maclaurin Series
Function Maclaurin Series Radius of Convergence e x e^x e x ∑ n = 0 ∞ x n n ! \displaystyle\sum_{n=0}^{\infty} \frac{x^n}{n!} n = 0 ∑ ∞ n ! x n ∞ \infty ∞ sin x \sin x sin x ∑ n = 0 ∞ ( − 1 ) n x 2 n + 1 ( 2 n + 1 ) ! \displaystyle\sum_{n=0}^{\infty} \frac{(-1)^n x^{2n+1}}{(2n+1)!} n = 0 ∑ ∞ ( 2 n + 1 )! ( − 1 ) n x 2 n + 1 ∞ \infty ∞ cos x \cos x cos x ∑ n = 0 ∞ ( − 1 ) n x 2 n ( 2 n ) ! \displaystyle\sum_{n=0}^{\infty} \frac{(-1)^n x^{2n}}{(2n)!} n = 0 ∑ ∞ ( 2 n )! ( − 1 ) n x 2 n ∞ \infty ∞ ln ( 1 + x ) \ln(1 + x) ln ( 1 + x ) ∑ n = 1 ∞ ( − 1 ) n + 1 x n n \displaystyle\sum_{n=1}^{\infty} \frac{(-1)^{n+1} x^n}{n} n = 1 ∑ ∞ n ( − 1 ) n + 1 x n 1 1 1 ( 1 + x ) n (1 + x)^n ( 1 + x ) n ∑ k = 0 ∞ ( n k ) x k \displaystyle\sum_{k=0}^{\infty} \binom{n}{k}x^k k = 0 ∑ ∞ ( k n ) x k 1 1 1 1 1 − x \dfrac{1}{1 - x} 1 − x 1 ∑ n = 0 ∞ x n \displaystyle\sum_{n=0}^{\infty} x^n n = 0 ∑ ∞ x n 1 1 1 arctan x \arctan x arctan x ∑ n = 0 ∞ ( − 1 ) n x 2 n + 1 2 n + 1 \displaystyle\sum_{n=0}^{\infty} \frac{(-1)^n x^{2n+1}}{2n+1} n = 0 ∑ ∞ 2 n + 1 ( − 1 ) n x 2 n + 1 1 1 1
Deriving Series
Example. Find the Maclaurin series of e x e^x e x .
f ( 0 ) = 1 , f ′ ( 0 ) = 1 , f ′ ′ ( 0 ) = 1 , … , f ( n ) ( 0 ) = 1 f(0) = 1, \quad f'(0) = 1, \quad f''(0) = 1, \quad \ldots, \quad f^{(n)}(0) = 1 f ( 0 ) = 1 , f ′ ( 0 ) = 1 , f ′′ ( 0 ) = 1 , … , f ( n ) ( 0 ) = 1
e x = 1 + x + x 2 2 ! + x 3 3 ! + ⋯ = ∑ n = 0 ∞ x n n ! e^x = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + \cdots = \sum_{n=0}^{\infty} \frac{x^n}{n!} e x = 1 + x + 2 ! x 2 + 3 ! x 3 + ⋯ = ∑ n = 0 ∞ n ! x n
Example. Find the Maclaurin series of sin x \sin x sin x .
f ( 0 ) = 0 , f ′ ( 0 ) = 1 , f ′ ′ ( 0 ) = 0 , f ′ ′ ′ ( 0 ) = − 1 , f ( 4 ) ( 0 ) = 0 , … f(0) = 0, \quad f'(0) = 1, \quad f''(0) = 0, \quad f'''(0) = -1, \quad f^{(4)}(0) = 0, \quad \ldots f ( 0 ) = 0 , f ′ ( 0 ) = 1 , f ′′ ( 0 ) = 0 , f ′′′ ( 0 ) = − 1 , f ( 4 ) ( 0 ) = 0 , …
sin x = x − x 3 3 ! + x 5 5 ! − x 7 7 ! + ⋯ = ∑ n = 0 ∞ ( − 1 ) n x 2 n + 1 ( 2 n + 1 ) ! \sin x = x - \frac{x^3}{3!} + \frac{x^5}{5!} - \frac{x^7}{7!} + \cdots = \sum_{n=0}^{\infty} \frac{(-1)^n x^{2n+1}}{(2n+1)!} sin x = x − 3 ! x 3 + 5 ! x 5 − 7 ! x 7 + ⋯ = ∑ n = 0 ∞ ( 2 n + 1 )! ( − 1 ) n x 2 n + 1
Maclaurin Series from Known Series
Example. Find the Maclaurin series of x 2 e x x^2 e^x x 2 e x .
Since e x = ∑ n = 0 ∞ x n n ! e^x = \displaystyle\sum_{n=0}^{\infty} \frac{x^n}{n!} e x = n = 0 ∑ ∞ n ! x n , multiplying by x 2 x^2 x 2 :
x 2 e x = ∑ n = 0 ∞ x n + 2 n ! = x 2 + x 3 + x 4 2 ! + x 5 3 ! + ⋯ x^2 e^x = \sum_{n=0}^{\infty} \frac{x^{n+2}}{n!} = x^2 + x^3 + \frac{x^4}{2!} + \frac{x^5}{3!} + \cdots x 2 e x = ∑ n = 0 ∞ n ! x n + 2 = x 2 + x 3 + 2 ! x 4 + 3 ! x 5 + ⋯
Example. Find the Maclaurin series of 1 1 + x 2 \dfrac{1}{1 + x^2} 1 + x 2 1 .
1 1 + x 2 = 1 − x 2 + x 4 − x 6 + ⋯ = ∑ n = 0 ∞ ( − 1 ) n x 2 n \frac{1}{1 + x^2} = 1 - x^2 + x^4 - x^6 + \cdots = \sum_{n=0}^{\infty} (-1)^n x^{2n} 1 + x 2 1 = 1 − x 2 + x 4 − x 6 + ⋯ = ∑ n = 0 ∞ ( − 1 ) n x 2 n
Integrating term by term gives the series for arctan x \arctan x arctan x :
arctan x = x − x 3 3 + x 5 5 − x 7 7 + ⋯ \arctan x = x - \frac{x^3}{3} + \frac{x^5}{5} - \frac{x^7}{7} + \cdots arctan x = x − 3 x 3 + 5 x 5 − 7 x 7 + ⋯
Taylor Series
Definition
The Taylor series of f f f about x = a x = a x = a is:
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 f ( x ) = ∑ n = 0 ∞ n ! f ( n ) ( a ) ( x − a ) n
This reduces to the Maclaurin series when a = 0 a = 0 a = 0 .
Taylor Polynomial Approximation
The n n n -th degree Taylor polynomial of f f f about a a a is:
T n ( x ) = ∑ k = 0 n f ( k ) ( a ) k ! ( x − a ) k T_n(x) = \sum_{k=0}^{n} \frac{f^{(k)}(a)}{k!}(x - a)^k T n ( x ) = ∑ k = 0 n k ! f ( k ) ( a ) ( x − a ) k
Lagrange Remainder
The error in approximating f ( x ) f(x) f ( x ) by T n ( x ) T_n(x) T n ( x ) is bounded by:
∣ R n ( x ) ∣ = ∣ f ( x ) − T n ( x ) ∣ ≤ M ∣ x − a ∣ n + 1 ( n + 1 ) ! |R_n(x)| = \left|f(x) - T_n(x)\right| \le \frac{M|x - a|^{n+1}}{(n+1)!} ∣ R n ( x ) ∣ = ∣ f ( x ) − T n ( x ) ∣ ≤ ( n + 1 )! M ∣ x − a ∣ n + 1
where M M M is an upper bound for ∣ f ( n + 1 ) ( t ) ∣ |f^{(n+1)}(t)| ∣ f ( n + 1 ) ( t ) ∣ for all t t t between a a a and x x x .
Example. Approximate e \sqrt{e} e using a 3rd degree Maclaurin polynomial and bound the error.
T 3 ( x ) = 1 + x + x 2 2 + x 3 6 T_3(x) = 1 + x + \dfrac{x^2}{2} + \dfrac{x^3}{6} T 3 ( x ) = 1 + x + 2 x 2 + 6 x 3 .
T 3 ( 0.5 ) = 1 + 0.5 + 0.125 + 0.020833 … = 1.64583 … T_3(0.5) = 1 + 0.5 + 0.125 + 0.020833\ldots = 1.64583\ldots T 3 ( 0.5 ) = 1 + 0.5 + 0.125 + 0.020833 … = 1.64583 …
True value: e 0.5 ≈ 1.64872 e^{0.5} \approx 1.64872 e 0.5 ≈ 1.64872 .
For the error bound, ∣ f ( 4 ) ( t ) ∣ = e t ≤ e 0.5 |f^{(4)}(t)| = e^t \le e^{0.5} ∣ f ( 4 ) ( t ) ∣ = e t ≤ e 0.5 for 0 ≤ t ≤ 0.5 0 \le t \le 0.5 0 ≤ t ≤ 0.5 :
∣ R 3 ( 0.5 ) ∣ ≤ e 0.5 ⋅ ( 0.5 ) 4 24 ≈ 1.649 ⋅ 0.0625 24 ≈ 0.0043 |R_3(0.5)| \le \frac{e^{0.5} \cdot (0.5)^4}{24} \approx \frac{1.649 \cdot 0.0625}{24} \approx 0.0043 ∣ R 3 ( 0.5 ) ∣ ≤ 24 e 0.5 ⋅ ( 0.5 ) 4 ≈ 24 1.649 ⋅ 0.0625 ≈ 0.0043
Actual error: ∣ 1.64872 − 1.64583 ∣ ≈ 0.0029 |1.64872 - 1.64583| \approx 0.0029 ∣1.64872 − 1.64583∣ ≈ 0.0029 , which is within the bound.
Proof by Induction
Structure
Mathematical induction proves a statement P ( n ) P(n) P ( n ) for all integers n ≥ n 0 n \ge n_0 n ≥ n 0 :
Base case: Verify P ( n 0 ) P(n_0) P ( n 0 ) is true.
Inductive hypothesis: Assume P ( k ) P(k) P ( k ) is true for some arbitrary k ≥ n 0 k \ge n_0 k ≥ n 0 .
Inductive step: Using the hypothesis, prove P ( k + 1 ) P(k + 1) P ( k + 1 ) is true.
Conclusion: By the principle of mathematical induction, P ( n ) P(n) P ( n ) is true for all n ≥ n 0 n \ge n_0 n ≥ n 0 .
Summation Proofs
Example. Prove that ∑ k = 1 n k 2 = n ( n + 1 ) ( 2 n + 1 ) 6 \displaystyle\sum_{k=1}^{n} k^2 = \frac{n(n+1)(2n+1)}{6} k = 1 ∑ n k 2 = 6 n ( n + 1 ) ( 2 n + 1 ) for all n ∈ ′ { ′ Z ′ } ′ + n \in \mathbb{'\{'}Z{'\}'}^+ n ∈ ′ { ′ Z ′ } ′ + .
Base case (n = 1 n = 1 n = 1 ): 1 ⋅ 2 ⋅ 3 6 = 1 \dfrac{1 \cdot 2 \cdot 3}{6} = 1 6 1 ⋅ 2 ⋅ 3 = 1 . True.
Inductive hypothesis: Assume ∑ k = 1 j k 2 = j ( j + 1 ) ( 2 j + 1 ) 6 \displaystyle\sum_{k=1}^{j} k^2 = \frac{j(j+1)(2j+1)}{6} k = 1 ∑ j k 2 = 6 j ( j + 1 ) ( 2 j + 1 ) for some j ≥ 1 j \ge 1 j ≥ 1 .
Inductive step:
∑ k = 1 j + 1 k 2 = ∑ k = 1 j k 2 + ( j + 1 ) 2 = j ( j + 1 ) ( 2 j + 1 ) 6 + ( j + 1 ) 2 \sum_{k=1}^{j+1} k^2 = \sum_{k=1}^{j} k^2 + (j+1)^2 = \frac{j(j+1)(2j+1)}{6} + (j+1)^2 ∑ k = 1 j + 1 k 2 = ∑ k = 1 j k 2 + ( j + 1 ) 2 = 6 j ( j + 1 ) ( 2 j + 1 ) + ( j + 1 ) 2
= ( j + 1 ) 6 [ j ( 2 j + 1 ) + 6 ( j + 1 ) ] = ( j + 1 ) 6 [ 2 j 2 + 7 j + 6 ] = \frac{(j+1)}{6}\bigl[j(2j+1) + 6(j+1)\bigr] = \frac{(j+1)}{6}\bigl[2j^2 + 7j + 6\bigr] = 6 ( j + 1 ) [ j ( 2 j + 1 ) + 6 ( j + 1 ) ] = 6 ( j + 1 ) [ 2 j 2 + 7 j + 6 ]
= ( j + 1 ) ( j + 2 ) ( 2 j + 3 ) 6 = \frac{(j+1)(j+2)(2j+3)}{6} = 6 ( j + 1 ) ( j + 2 ) ( 2 j + 3 )
This is the formula with n = j + 1 n = j + 1 n = j + 1 . Hence P ( j + 1 ) P(j+1) P ( j + 1 ) is true. By induction, the result holds for
all n ∈ ′ { ′ Z ′ } ′ + n \in \mathbb{'\{'}Z{'\}'}^+ n ∈ ′ { ′ Z ′ } ′ + .
Divisibility Proofs
Example. Prove that 3 n − 1 3^n - 1 3 n − 1 is divisible by 2 2 2 for all n ∈ ′ { ′ N ′ } ′ n \in \mathbb{'\{'}N{'\}'} n ∈ ′ { ′ N ′ } ′ .
Base case (n = 0 n = 0 n = 0 ): 3 0 − 1 = 0 3^0 - 1 = 0 3 0 − 1 = 0 , which is divisible by 2 2 2 . True.
Inductive hypothesis: 3 k − 1 = 2 m 3^k - 1 = 2m 3 k − 1 = 2 m for some m ∈ ′ { ′ Z ′ } ′ m \in \mathbb{'\{'}Z{'\}'} m ∈ ′ { ′ Z ′ } ′ .
Inductive step:
3 k + 1 − 1 = 3 ⋅ 3 k − 1 = 3 ( 2 m + 1 ) − 1 = 6 m + 3 − 1 = 6 m + 2 = 2 ( 3 m + 1 ) 3^{k+1} - 1 = 3 \cdot 3^k - 1 = 3(2m + 1) - 1 = 6m + 3 - 1 = 6m + 2 = 2(3m + 1) 3 k + 1 − 1 = 3 ⋅ 3 k − 1 = 3 ( 2 m + 1 ) − 1 = 6 m + 3 − 1 = 6 m + 2 = 2 ( 3 m + 1 )
This is divisible by 2 2 2 . By induction, the result holds.
Inequality Proofs
Example. Prove that 2 n > n 2^n \gt n 2 n > n for all n ∈ ′ { ′ Z ′ } ′ + n \in \mathbb{'\{'}Z{'\}'}^+ n ∈ ′ { ′ Z ′ } ′ + .
Base case (n = 1 n = 1 n = 1 ): 2 1 = 2 > 1 2^1 = 2 \gt 1 2 1 = 2 > 1 . True.
Inductive hypothesis: 2 k > k 2^k \gt k 2 k > k for some k ≥ 1 k \ge 1 k ≥ 1 .
Inductive step:
2 k + 1 = 2 ⋅ 2 k > 2 k ≥ k + 1 2^{k+1} = 2 \cdot 2^k \gt 2k \ge k + 1 2 k + 1 = 2 ⋅ 2 k > 2 k ≥ k + 1
(The last inequality holds since k ≥ 1 k \ge 1 k ≥ 1 .) Therefore 2 k + 1 > k + 1 2^{k+1} \gt k + 1 2 k + 1 > k + 1 . By induction, 2 n > n 2^n \gt n 2 n > n
for all positive integers n n n .
Common Pitfall
The inductive step must genuinely use the inductive hypothesis. Simply proving P ( k + 1 ) P(k+1) P ( k + 1 ) independently
of P ( k ) P(k) P ( k ) is not a valid induction argument. Always make it explicit where the hypothesis is used.
Additional Worked Examples
Worked Example: Convergence of a Series by Ratio Test
Determine whether ∑ n = 1 ∞ n ! 10 n \displaystyle\sum_{n=1}^{\infty} \frac{n!}{10^n} n = 1 ∑ ∞ 1 0 n n ! converges or diverges.
Solution Apply the ratio test:
L = lim n → ∞ ( n + 1 ) ! / 10 n + 1 n ! / 10 n = lim n → ∞ ( n + 1 ) ! ⋅ 10 n n ! ⋅ 10 n + 1 = lim n → ∞ n + 1 10 = ∞ L = \lim_{n \to \infty} \frac{(n+1)! / 10^{n+1}}{n! / 10^n} = \lim_{n \to \infty} \frac{(n+1)! \cdot 10^n}{n! \cdot 10^{n+1}} = \lim_{n \to \infty} \frac{n+1}{10} = \infty L = lim n → ∞ n ! /1 0 n ( n + 1 )! /1 0 n + 1 = lim n → ∞ n ! ⋅ 1 0 n + 1 ( n + 1 )! ⋅ 1 0 n = lim n → ∞ 10 n + 1 = ∞
Since L > 1 L \gt 1 L > 1 , the series diverges by the ratio test.
Worked Example: Maclaurin Series of a Composite Function
Find the Maclaurin series of f ( x ) = e − x 2 f(x) = e^{-x^2} f ( x ) = e − x 2 up to the term in x 6 x^6 x 6 , and use it to approximate
∫ 0 0.5 e − x 2 d x \displaystyle\int_0^{0.5} e^{-x^2}\,dx ∫ 0 0.5 e − x 2 d x .
Solution Substitute − x 2 -x^2 − x 2 into the Maclaurin series for e u e^u e u :
e − x 2 = 1 + ( − x 2 ) + ( − x 2 ) 2 2 ! + ( − x 2 ) 3 3 ! + ⋯ = 1 − x 2 + x 4 2 − x 6 6 + ⋯ e^{-x^2} = 1 + (-x^2) + \frac{(-x^2)^2}{2!} + \frac{(-x^2)^3}{3!} + \cdots = 1 - x^2 + \frac{x^4}{2} - \frac{x^6}{6} + \cdots e − x 2 = 1 + ( − x 2 ) + 2 ! ( − x 2 ) 2 + 3 ! ( − x 2 ) 3 + ⋯ = 1 − x 2 + 2 x 4 − 6 x 6 + ⋯
Integrate term by term from 0 0 0 to 0.5 0.5 0.5 :
∫ 0 0.5 e − x 2 d x ≈ ∫ 0 0.5 ( 1 − x 2 + x 4 2 − x 6 6 ) d x \int_0^{0.5} e^{-x^2}\,dx \approx \int_0^{0.5} \left(1 - x^2 + \frac{x^4}{2} - \frac{x^6}{6}\right)dx ∫ 0 0.5 e − x 2 d x ≈ ∫ 0 0.5 ( 1 − x 2 + 2 x 4 − 6 x 6 ) d x
= [ x − x 3 3 + x 5 10 − x 7 42 ] 0 0.5 = \left[x - \frac{x^3}{3} + \frac{x^5}{10} - \frac{x^7}{42}\right]_0^{0.5} = [ x − 3 x 3 + 10 x 5 − 42 x 7 ] 0 0.5
= 0.5 − 0.125 3 + 0.03125 10 − 0.0078125 42 = 0.5 - \frac{0.125}{3} + \frac{0.03125}{10} - \frac{0.0078125}{42} = 0.5 − 3 0.125 + 10 0.03125 − 42 0.0078125
= 0.5 − 0.041667 + 0.003125 − 0.000186 ≈ 0.4613 = 0.5 - 0.041667 + 0.003125 - 0.000186 \approx 0.4613 = 0.5 − 0.041667 + 0.003125 − 0.000186 ≈ 0.4613
The actual value of the error function at 0.5 0.5 0.5 gives approximately 0.4613 0.4613 0.4613 , confirming the accuracy
of this approximation.
Worked Example: General Binomial Expansion to Find a Coefficient
Find the coefficient of x 4 x^4 x 4 in the expansion of ( 1 − 2 x ) − 3 (1 - 2x)^{-3} ( 1 − 2 x ) − 3 .
Solution ( 1 + x ) n = 1 + n x + n ( n − 1 ) 2 ! x 2 + n ( n − 1 ) ( n − 2 ) 3 ! x 3 + n ( n − 1 ) ( n − 2 ) ( n − 3 ) 4 ! x 4 + ⋯ (1 + x)^n = 1 + nx + \frac{n(n-1)}{2!}x^2 + \frac{n(n-1)(n-2)}{3!}x^3 + \frac{n(n-1)(n-2)(n-3)}{4!}x^4 + \cdots ( 1 + x ) n = 1 + n x + 2 ! n ( n − 1 ) x 2 + 3 ! n ( n − 1 ) ( n − 2 ) x 3 + 4 ! n ( n − 1 ) ( n − 2 ) ( n − 3 ) x 4 + ⋯
Here n = − 3 n = -3 n = − 3 and we substitute x → − 2 x x \to -2x x → − 2 x :
( 1 − 2 x ) − 3 = 1 + ( − 3 ) ( − 2 x ) + ( − 3 ) ( − 4 ) 2 ! ( − 2 x ) 2 + ( − 3 ) ( − 4 ) ( − 5 ) 3 ! ( − 2 x ) 3 + ( − 3 ) ( − 4 ) ( − 5 ) ( − 6 ) 4 ! ( − 2 x ) 4 + ⋯ (1 - 2x)^{-3} = 1 + (-3)(-2x) + \frac{(-3)(-4)}{2!}(-2x)^2 + \frac{(-3)(-4)(-5)}{3!}(-2x)^3 + \frac{(-3)(-4)(-5)(-6)}{4!}(-2x)^4 + \cdots ( 1 − 2 x ) − 3 = 1 + ( − 3 ) ( − 2 x ) + 2 ! ( − 3 ) ( − 4 ) ( − 2 x ) 2 + 3 ! ( − 3 ) ( − 4 ) ( − 5 ) ( − 2 x ) 3 + 4 ! ( − 3 ) ( − 4 ) ( − 5 ) ( − 6 ) ( − 2 x ) 4 + ⋯
The x 4 x^4 x 4 coefficient:
( − 3 ) ( − 4 ) ( − 5 ) ( − 6 ) 24 ⋅ ( − 2 ) 4 = 360 24 ⋅ 16 = 15 ⋅ 16 = 240 \frac{(-3)(-4)(-5)(-6)}{24} \cdot (-2)^4 = \frac{360}{24} \cdot 16 = 15 \cdot 16 = 240 24 ( − 3 ) ( − 4 ) ( − 5 ) ( − 6 ) ⋅ ( − 2 ) 4 = 24 360 ⋅ 16 = 15 ⋅ 16 = 240
So the coefficient of x 4 x^4 x 4 is 240 240 240 .
Worked Example: Induction Proof Involving Summation
Prove by induction that ∑ k = 1 n k ⋅ 2 k − 1 = ( n − 1 ) ⋅ 2 n + 1 \displaystyle\sum_{k=1}^{n} k \cdot 2^{k-1} = (n - 1) \cdot 2^n + 1 k = 1 ∑ n k ⋅ 2 k − 1 = ( n − 1 ) ⋅ 2 n + 1 for all
n ∈ ′ { ′ Z ′ } ′ + n \in \mathbb{'\{'}Z{'\}'}^+ n ∈ ′ { ′ Z ′ } ′ + .
Solution Base case (n = 1 n = 1 n = 1 ): LHS = 1 ⋅ 2 0 = 1 = 1 \cdot 2^0 = 1 = 1 ⋅ 2 0 = 1 . RHS = ( 1 − 1 ) ⋅ 2 1 + 1 = 1 = (1 - 1) \cdot 2^1 + 1 = 1 = ( 1 − 1 ) ⋅ 2 1 + 1 = 1 . True.
Inductive hypothesis: Assume ∑ k = 1 j k ⋅ 2 k − 1 = ( j − 1 ) ⋅ 2 j + 1 \displaystyle\sum_{k=1}^{j} k \cdot 2^{k-1} = (j - 1) \cdot 2^j + 1 k = 1 ∑ j k ⋅ 2 k − 1 = ( j − 1 ) ⋅ 2 j + 1 for some
j ≥ 1 j \ge 1 j ≥ 1 .
Inductive step:
∑ k = 1 j + 1 k ⋅ 2 k − 1 = ∑ k = 1 j k ⋅ 2 k − 1 + ( j + 1 ) ⋅ 2 j \sum_{k=1}^{j+1} k \cdot 2^{k-1} = \sum_{k=1}^{j} k \cdot 2^{k-1} + (j+1) \cdot 2^j ∑ k = 1 j + 1 k ⋅ 2 k − 1 = ∑ k = 1 j k ⋅ 2 k − 1 + ( j + 1 ) ⋅ 2 j
= ( j − 1 ) ⋅ 2 j + 1 + ( j + 1 ) ⋅ 2 j ( b y h y p o t h e s i s ) = (j - 1) \cdot 2^j + 1 + (j+1) \cdot 2^j \quad \mathrm{(by\ hypothesis)} = ( j − 1 ) ⋅ 2 j + 1 + ( j + 1 ) ⋅ 2 j ( by hypothesis )
= [ ( j − 1 ) + ( j + 1 ) ] 2 j + 1 = 2 j ⋅ 2 j + 1 = j ⋅ 2 j + 1 + 1 = \bigl[(j-1) + (j+1)\bigr] 2^j + 1 = 2j \cdot 2^j + 1 = j \cdot 2^{j+1} + 1 = [ ( j − 1 ) + ( j + 1 ) ] 2 j + 1 = 2 j ⋅ 2 j + 1 = j ⋅ 2 j + 1 + 1
= ( j + 1 − 1 ) ⋅ 2 j + 1 + 1 = (j + 1 - 1) \cdot 2^{j+1} + 1 = ( j + 1 − 1 ) ⋅ 2 j + 1 + 1
This is the formula with n = j + 1 n = j + 1 n = j + 1 . By induction, the result holds for all n ∈ ′ { ′ Z ′ } ′ + n \in \mathbb{'\{'}Z{'\}'}^+ n ∈ ′ { ′ Z ′ } ′ + .
Worked Example: Taylor Series Error Bound
Use a second degree Taylor polynomial of ln ( 1 + x ) \ln(1 + x) ln ( 1 + x ) about x = 0 x = 0 x = 0 to approximate ln ( 1.2 ) \ln(1.2) ln ( 1.2 ) . Bound
the error.
Solution f ( x ) = ln ( 1 + x ) , f ′ ( x ) = 1 1 + x , f ′ ′ ( x ) = − 1 ( 1 + x ) 2 , f ′ ′ ′ ( x ) = 2 ( 1 + x ) 3 f(x) = \ln(1 + x), \quad f'(x) = \frac{1}{1+x}, \quad f''(x) = \frac{-1}{(1+x)^2}, \quad f'''(x) = \frac{2}{(1+x)^3} f ( x ) = ln ( 1 + x ) , f ′ ( x ) = 1 + x 1 , f ′′ ( x ) = ( 1 + x ) 2 − 1 , f ′′′ ( x ) = ( 1 + x ) 3 2
T 2 ( x ) = f ( 0 ) + f ′ ( 0 ) x + f ′ ′ ( 0 ) 2 x 2 = 0 + x − x 2 2 T_2(x) = f(0) + f'(0)x + \frac{f''(0)}{2}x^2 = 0 + x - \frac{x^2}{2} T 2 ( x ) = f ( 0 ) + f ′ ( 0 ) x + 2 f ′′ ( 0 ) x 2 = 0 + x − 2 x 2
T 2 ( 0.2 ) = 0.2 − 0.04 2 = 0.2 − 0.02 = 0.18 T_2(0.2) = 0.2 - \frac{0.04}{2} = 0.2 - 0.02 = 0.18 T 2 ( 0.2 ) = 0.2 − 2 0.04 = 0.2 − 0.02 = 0.18
True value: ln ( 1.2 ) ≈ 0.1823 \ln(1.2) \approx 0.1823 ln ( 1.2 ) ≈ 0.1823 .
For the error bound on [ 0 , 0.2 ] [0, 0.2] [ 0 , 0.2 ] : ∣ f ′ ′ ′ ( t ) ∣ = 2 ( 1 + t ) 3 ≤ 2 |f'''(t)| = \dfrac{2}{(1+t)^3} \le 2 ∣ f ′′′ ( t ) ∣ = ( 1 + t ) 3 2 ≤ 2 for 0 ≤ t ≤ 0.2 0 \le t \le 0.2 0 ≤ t ≤ 0.2 .
∣ R 2 ( 0.2 ) ∣ ≤ 2 ⋅ ( 0.2 ) 3 6 = 2 ⋅ 0.008 6 ≈ 0.00267 |R_2(0.2)| \le \frac{2 \cdot (0.2)^3}{6} = \frac{2 \cdot 0.008}{6} \approx 0.00267 ∣ R 2 ( 0.2 ) ∣ ≤ 6 2 ⋅ ( 0.2 ) 3 = 6 2 ⋅ 0.008 ≈ 0.00267
Actual error: ∣ 0.1823 − 0.18 ∣ = 0.0023 |0.1823 - 0.18| = 0.0023 ∣0.1823 − 0.18∣ = 0.0023 , which is within the bound.
Common Pitfalls
Misidentifying the first term in sigma notation. ∑ k = 0 n \sum_{k=0}^{n} ∑ k = 0 n has n + 1 n + 1 n + 1 terms, while
∑ k = 1 n \sum_{k=1}^{n} ∑ k = 1 n has n n n terms. Confusing the starting index leads to off-by-one errors in sums.
Applying the infinite sum formula when ∣ r ∣ ≥ 1 |r| \ge 1 ∣ r ∣ ≥ 1 . The formula S ∞ = a 1 1 − r S_{\infty} = \dfrac{a_1}{1 - r} S ∞ = 1 − r a 1
is valid only when ∣ r ∣ < 1 |r| \lt 1 ∣ r ∣ < 1 . For ∣ r ∣ ≥ 1 |r| \ge 1 ∣ r ∣ ≥ 1 the series diverges and the formula is
meaningless.
Computing the wrong term number. The n n n -th term of a geometric sequence is
a 1 r n − 1 a_1 r^{n-1} a 1 r n − 1 , not a 1 r n a_1 r^n a 1 r n . Similarly, the n n n -th term of an arithmetic sequence is
a 1 + ( n − 1 ) d a_1 + (n-1)d a 1 + ( n − 1 ) d , not a 1 + n d a_1 + nd a 1 + n d .
Using the ratio test when L = 1 L = 1 L = 1 . The ratio test is inconclusive when L = 1 L = 1 L = 1 . The series
∑ 1 n \sum \dfrac{1}{n} ∑ n 1 diverges and ∑ 1 n 2 \sum \dfrac{1}{n^2} ∑ n 2 1 converges, yet both give L = 1 L = 1 L = 1 .
Weak base case in induction. The base case must match the claim. If the statement starts at
n = 1 n = 1 n = 1 , proving it for n = 0 n = 0 n = 0 is not sufficient unless the domain is specified to include 0 0 0 .
Neglecting the alternating sign in the general binomial expansion. When n n n is not a positive
integer, the series is infinite and the sign of each coefficient depends on the value of n n n .
Substituting x → a x x \to ax x → a x also changes the sign of odd powers when a < 0 a \lt 0 a < 0 .
Confusing the Lagrange remainder with the actual error. The remainder bound ∣ R n ( x ) ∣ ≤ M ∣ x − a ∣ n + 1 ( n + 1 ) ! |R_n(x)| \le
\dfrac{M|x-a|^{n+1}}{(n+1)!} ∣ R n ( x ) ∣ ≤ ( n + 1 )! M ∣ x − a ∣ n + 1 gives an upper bound , not the exact error. The actual error may
be much smaller.
Forgetting convergence conditions for Maclaurin series. Each standard Maclaurin series has a
specific radius of convergence. The series for ln ( 1 + x ) \ln(1+x) ln ( 1 + x ) only converges for − 1 < x ≤ 1 -1 \lt x \le 1 − 1 < x ≤ 1 ;
using it outside this interval gives incorrect results.
Exam-Style Problems
Find the sum of the infinite geometric series 8 − 4 + 2 − 1 + ⋯ 8 - 4 + 2 - 1 + \cdots 8 − 4 + 2 − 1 + ⋯ and express the repeating
decimal 0. 27 ‾ 0.\overline{27} 0. 27 as a fraction in lowest terms.
Use the ratio test to determine the convergence of ∑ n = 1 ∞ 3 n n ! \displaystyle\sum_{n=1}^{\infty} \frac{3^n}{n!} n = 1 ∑ ∞ n ! 3 n .
Find the coefficient of x 5 x^5 x 5 in the expansion of ( 1 + 3 x ) − 2 (1 + 3x)^{-2} ( 1 + 3 x ) − 2 .
Prove by induction that ∑ k = 1 n 1 k ( k + 1 ) = n n + 1 \displaystyle\sum_{k=1}^{n} \frac{1}{k(k+1)} = \frac{n}{n+1} k = 1 ∑ n k ( k + 1 ) 1 = n + 1 n for all
n ∈ ′ { ′ Z ′ } ′ + n \in \mathbb{'\{'}Z{'\}'}^+ n ∈ ′ { ′ Z ′ } ′ + .
Find the Maclaurin series of x 1 + x 2 \dfrac{x}{1 + x^2} 1 + x 2 x up to x 7 x^7 x 7 and state the radius of convergence.
Use a third degree Maclaurin polynomial of cos x \cos x cos x to approximate cos ( 0.3 ) \cos(0.3) cos ( 0.3 ) . Bound the error
using the Lagrange remainder.
An arithmetic sequence has first term 5 5 5 and common difference 3 3 3 . A geometric sequence has
first term 2 2 2 and common ratio 2 2 2 . Find the smallest n n n for which the n n n -th term of the
geometric sequence exceeds the n n n -th term of the arithmetic sequence.
Determine whether ∑ n = 1 ∞ ( − 1 ) n n \displaystyle\sum_{n=1}^{\infty} \frac{(-1)^n}{\sqrt{n}} n = 1 ∑ ∞ n ( − 1 ) n converges absolutely,
converges conditionally, or diverges.
Cross-References
Differentiation is needed to derive Maclaurin and Taylor series: see Differentiation
Integration connects to term-by-term integration of power series: see Integration
Differential equations use series expansions as solution methods: see Differential Equations
Proof and reasoning techniques including induction: see Proof