Taylor Series: Formula, Examples And Convergence

#Calculus
TL;DR
A Taylor series rewrites a function as an infinite sum of power terms built from the function's derivatives at a single point aa: f(x)=∑n=0∞f(n)(a)n factorial(x−a)nf(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(a)}{n\text{ factorial}}(x-a)^n. When the centre is a=0a = 0 the same formula is called a Maclaurin series. Truncating the sum after a few terms is how calculators evaluate exe^x, sin⁡x\sin x, and cos⁡x\cos x.
BT
Bhanzu TeamLast updated on September 23, 202612 min read

What Is A Taylor Series?

A Taylor series is a way of writing a function as an infinite sum of power terms, where each term is built from one of the function's derivatives measured at a single point. That point is called the centre and is written aa. The formal statement is:

f(x)=∑n=0∞f(n)(a)n factorial(x−a)n=f(a)+f′(a)(x−a)+f′′(a)2(x−a)2+f′′′(a)6(x−a)3+⋯f(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(a)}{n\text{ factorial}}(x-a)^n = f(a) + f'(a)(x-a) + \frac{f''(a)}{2}(x-a)^2 + \frac{f'''(a)}{6}(x-a)^3 + \cdots

Here f(n)(a)f^{(n)}(a) is the nn-th derivative of ff evaluated at the centre, and the denominators are the factorials: 2 factorial=22\text{ factorial} = 2, 3 factorial=63\text{ factorial} = 6, 4 factorial=244\text{ factorial} = 24, and so on. Each derivative contributes exactly one term.

The idea is simple to state. If you know the height of a function at aa, its slope at aa, how the slope is bending at aa, and so on through every derivative, then you know the whole function near aa. The Taylor series is the recipe that turns that pile of derivative information back into the function.

When the centre is chosen at a=0a = 0, the formula becomes the special case known as a Maclaurin series:

f(x)=∑n=0∞f(n)(0)n factorialxn=f(0)+f′(0)x+f′′(0)2x2+f′′′(0)6x3+⋯f(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(0)}{n\text{ factorial}}x^n = f(0) + f'(0)x + \frac{f''(0)}{2}x^2 + \frac{f'''(0)}{6}x^3 + \cdots

A Maclaurin series is just a Taylor series centred at zero. Most of the famous expansions (exe^x, sin⁡x\sin x, cos⁡x\cos x) are quoted in this centred-at-zero form because the numbers come out cleanest there.

How Do You Find A Taylor Series?

To find a Taylor series, follow four fixed steps. The whole method is a bookkeeping loop over the derivative.

  • Differentiate repeatedly. Compute f(x)f(x), f′(x)f'(x), f′′(x)f''(x), f′′′(x)f'''(x), and so on, as many derivatives as you need terms.

  • Evaluate at the centre. Substitute x=ax = a into each derivative to get the numbers f(a)f(a), f′(a)f'(a), f′′(a)f''(a), ...

  • Divide by the factorial. The coefficient of the nn-th term is f(n)(a)n factorial\dfrac{f^{(n)}(a)}{n\text{ factorial}}.

  • Attach the power. Multiply each coefficient by (x−a)n(x-a)^n and add the terms.

Example 1: Build the Taylor series of exe^x at a=0a = 0.

The function f(x)=exf(x) = e^x is its own derivative, so every derivative is exe^x:

f(x)=ex,f′(x)=ex,f′′(x)=ex,f′′′(x)=ex,…f(x) = e^x, \quad f'(x) = e^x, \quad f''(x) = e^x, \quad f'''(x) = e^x, \dots

Evaluate each at the centre x=0x = 0. Since e0=1e^0 = 1, every value is 11:

f(0)=1,f′(0)=1,f′′(0)=1,f′′′(0)=1,…f(0) = 1, \quad f'(0) = 1, \quad f''(0) = 1, \quad f'''(0) = 1, \dots

Divide each by its factorial and attach the power:

ex=1+x+x22+x36+x424+⋯=∑n=0∞xnn factoriale^x = 1 + x + \frac{x^2}{2} + \frac{x^3}{6} + \frac{x^4}{24} + \cdots = \sum_{n=0}^{\infty} \frac{x^n}{n\text{ factorial}}

Final answer: ex=∑n=0∞xnn factoriale^x = \displaystyle\sum_{n=0}^{\infty} \frac{x^n}{n\text{ factorial}}, valid for every real number xx.

The geometric picture sits alongside the algebra. The first term 11 is the flat line through the point, adding xx tilts it into the tangent line, and adding x22\frac{x^2}{2} bends it into a parabola matching the curve. Every extra term forces one more derivative to agree at aa, so the polynomial hugs the true curve more tightly the more terms you keep.

What Are The Standard Taylor Series Expansions?

A handful of Maclaurin series appear so often that they are worth memorising. Each is found by the four-step method above, and each carries its own interval where the sum actually equals the function.

Table: Standard Maclaurin series (centre a=0a = 0) and where each one converges.

Function

Maclaurin series (first terms and general pattern)

Converges for

exe^x

1+x+x22+x36+⋯=∑xnn factorial1 + x + \dfrac{x^2}{2} + \dfrac{x^3}{6} + \cdots = \sum \dfrac{x^n}{n\text{ factorial}}

all real xx

sin⁡x\sin x

x−x36+x5120−x75040+⋯x - \dfrac{x^3}{6} + \dfrac{x^5}{120} - \dfrac{x^7}{5040} + \cdots

all real xx

cos⁡x\cos x

1−x22+x424−x6720+⋯1 - \dfrac{x^2}{2} + \dfrac{x^4}{24} - \dfrac{x^6}{720} + \cdots

all real xx

11−x\dfrac{1}{1-x}

1+x+x2+x3+⋯=∑xn1 + x + x^2 + x^3 + \cdots = \sum x^n

∣x∣<1\lvert x \rvert < 1

ln⁡(1+x)\ln(1+x)

x−x22+x33−x44+⋯x - \dfrac{x^2}{2} + \dfrac{x^3}{3} - \dfrac{x^4}{4} + \cdots

−1<x≤1-1 < x \le 1

(1+x)k(1+x)^k

1+kx+k(k−1)2x2+⋯1 + kx + \dfrac{k(k-1)}{2}x^2 + \cdots (the binomial series)

∣x∣<1\lvert x \rvert < 1

Two of these deserve a note. The series for 11−x\dfrac{1}{1-x} is exactly the geometric sequence summed to infinity, and it only equals the function inside ∣x∣<1\lvert x \rvert < 1. The last row is the binomial theorem extended to any exponent kk, including fractions and negatives.

Example 2: Derive the Maclaurin series of cos⁡x\cos x and verify the coefficients.

Differentiate cos⁡x\cos x four times, watching the pattern cycle:

f(x)=cos⁡x,f′(x)=−sin⁡x,f′′(x)=−cos⁡x,f′′′(x)=sin⁡x,f(4)(x)=cos⁡xf(x) = \cos x, \quad f'(x) = -\sin x, \quad f''(x) = -\cos x, \quad f'''(x) = \sin x, \quad f^{(4)}(x) = \cos x

Evaluate each at x=0x = 0, using cos⁡0=1\cos 0 = 1 and sin⁡0=0\sin 0 = 0:

f(0)=1,f′(0)=0,f′′(0)=−1,f′′′(0)=0,f(4)(0)=1f(0) = 1, \quad f'(0) = 0, \quad f''(0) = -1, \quad f'''(0) = 0, \quad f^{(4)}(0) = 1

Only the even derivatives survive, alternating in sign. Divide by the factorials:

cos⁡x=1−x22+x424−x6720+⋯\cos x = 1 - \frac{x^2}{2} + \frac{x^4}{24} - \frac{x^6}{720} + \cdots

Final answer: cos⁡x=1−x22+x424−x6720+⋯\cos x = 1 - \dfrac{x^2}{2} + \dfrac{x^4}{24} - \dfrac{x^6}{720} + \cdots, valid for all real xx. The same repeated-differentiation method gives the trigonometric derivatives that drive the sin⁡x\sin x expansion.

How Do You Write A Taylor Series Away From Zero?

Not every function is cleanest at a=0a = 0. The logarithm, for instance, is undefined at 00, so its Taylor series must be centred somewhere it lives, such as a=1a = 1.

Example 3: Find the Taylor series of ln⁡x\ln x centred at a=1a = 1.

Differentiate and evaluate at the centre x=1x = 1:

f(x)=ln⁡x,f′(x)=1x,f′′(x)=−1x2,f′′′(x)=2x3f(x) = \ln x, \quad f'(x) = \frac{1}{x}, \quad f''(x) = -\frac{1}{x^2}, \quad f'''(x) = \frac{2}{x^3}

f(1)=0,f′(1)=1,f′′(1)=−1,f′′′(1)=2f(1) = 0, \quad f'(1) = 1, \quad f''(1) = -1, \quad f'''(1) = 2

Divide by the factorials and attach powers of (x−1)(x - 1):

ln⁡x=(x−1)−(x−1)22+(x−1)33−(x−1)44+⋯\ln x = (x-1) - \frac{(x-1)^2}{2} + \frac{(x-1)^3}{3} - \frac{(x-1)^4}{4} + \cdots

Final answer: ln⁡x=(x−1)−(x−1)22+(x−1)33−⋯\ln x = (x-1) - \dfrac{(x-1)^2}{2} + \dfrac{(x-1)^3}{3} - \cdots, valid for 0<x≤20 < x \le 2.

Notice this is the same shape as the ln⁡(1+x)\ln(1+x) row of the table, because substituting u=x−1u = x - 1 turns one into the other. Whenever the centre is not zero, every power is (x−a)(x - a), never a bare xx.

What Is Taylor's Theorem And The Remainder?

A truncated Taylor series (a Taylor polynomial) is only an approximation. Taylor's theorem states exactly how large the leftover error is.

Taylor's theorem (Lagrange form of the remainder). If ff has n+1n+1 continuous derivatives on an interval containing the centre aa and the point xx, then

f(x)=∑k=0nf(k)(a)k factorial(x−a)k⏟Taylor polynomial Tn(x)+Rn(x),Rn(x)=f(n+1)(c)(n+1) factorial(x−a)n+1f(x) = \underbrace{\sum_{k=0}^{n} \frac{f^{(k)}(a)}{k\text{ factorial}}(x-a)^k}_{\text{Taylor polynomial } T_n(x)} + R_n(x), \qquad R_n(x) = \frac{f^{(n+1)}(c)}{(n+1)\text{ factorial}}(x-a)^{n+1}

for some point cc strictly between aa and xx. The term Rn(x)R_n(x) is the remainder, the exact gap between the function and its degree-nn polynomial.

The infinite Taylor series equals f(x)f(x) precisely when this remainder shrinks to zero: Rn(x)→0R_n(x) \to 0 as n→∞n \to \infty. For exe^x, sin⁡x\sin x, and cos⁡x\cos x that happens for every real xx, which is why those three converge everywhere.

Example 4: Approximate e0.5e^{0.5} and bound the error.

Use the exe^x series from Example 1 through the x4x^4 term, with x=0.5x = 0.5:

e0.5≈1+0.5+0.522+0.536+0.5424=1+0.5+0.125+0.0208+0.0026e^{0.5} \approx 1 + 0.5 + \frac{0.5^2}{2} + \frac{0.5^3}{6} + \frac{0.5^4}{24} = 1 + 0.5 + 0.125 + 0.0208 + 0.0026

e0.5≈1.6484e^{0.5} \approx 1.6484

The true value is e0.5=1.6487e^{0.5} = 1.6487 to 4 decimal places, so the estimate is already within 0.00030.0003. The remainder bound confirms this: since the fifth derivative of exe^x is ex≤e0.5<2e^x \le e^{0.5} < 2 on [0,0.5][0, 0.5],

∣R4∣≤2⋅0.555 factorial=2⋅0.03125120≈0.00052\lvert R_4 \rvert \le \frac{2 \cdot 0.5^5}{5\text{ factorial}} = \frac{2 \cdot 0.03125}{120} \approx 0.00052

Final answer: e0.5≈1.6484e^{0.5} \approx 1.6484, with a guaranteed error below 0.000520.00052. The actual error, 0.00030.0003, sits comfortably inside that bound.

Why Does A Taylor Series Work?

The construction is not a lucky guess. It is forced by one demand: make a polynomial whose derivatives all match the function's derivatives at the centre.

  • Term nn controls derivative nn. The coefficient f(n)(a)n factorial\frac{f^{(n)}(a)}{n\text{ factorial}} is chosen so that when you differentiate the polynomial nn times and set x=ax = a, you recover exactly f(n)(a)f^{(n)}(a). The factorial cancels the number that repeated differentiation of (x−a)n(x-a)^n throws out.

  • Each term corrects the one before. The constant fixes the height, the linear term fixes the slope, the quadratic fixes the curvature, and so on down the list of derivatives.

  • Powers of (x−a)(x-a) stay small near the centre. Close to aa, the term (x−a)n(x-a)^n is tiny for large nn, so the early terms dominate and a short polynomial is already accurate.

Geometrically, the degree-1 Taylor polynomial is the tangent line, the arithmetic version of "zoom in until the curve looks straight." The degree-2 polynomial is the parabola that shares the curve's bending. Higher degrees keep adding matched behaviour, so the polynomial and the function become indistinguishable over a widening stretch around aa. Taylor series are the exact statement of what "looks like the curve near this point" means.

Who Invented The Taylor Series?

The formula carries one name, but the idea passed through several hands, and the earliest of them worked far from Europe.

Two named figures anchor the modern account:

  • Brook Taylor (1685–1731, England) stated the general expansion in his 1715 work Methodus Incrementorum Directa et Inversa, giving the series its name.

  • Colin Maclaurin (1698–1746, Scotland) made such heavy use of the centre-at-zero special case that it now carries his name, even though it is only Taylor's formula with a=0a = 0.

Where Is The Taylor Series Used In The Real World?

Truncated Taylor series are one of the most reused tools in applied mathematics, precisely because they turn hard functions into easy polynomials.

  • Calculators and computers: transcendental functions like sin⁡x\sin x, cos⁡x\cos x, exe^x, and ln⁡x\ln x have no finite formula, so hardware evaluates a truncated Taylor (or closely related) series to the required number of digits.

  • Physics: the small-angle approximation sin⁡θ≈θ\sin \theta \approx \theta is just the first Taylor term, and it underlies pendulum motion, optics, and much of engineering mechanics.

  • Numerical methods: solving differential equations by Euler's method or Runge-Kutta rests on Taylor expansions, as does numerical integration.

  • Economics and finance: option-pricing models are approximated by Taylor expansions to estimate how a price responds to small changes in its inputs.

  • Machine learning: gradient-based training uses the first Taylor term (the gradient), and second-order methods use the next term (the curvature) to step toward a minimum.

One recipe, adding up a few derivatives, quietly runs the screen you are reading this on, the physics of a swinging pendulum, and the training of large models. That reach across unrelated fields is the signature of a deep idea.

What Are The Most Common Mistakes With A Taylor Series?

These four errors account for most lost marks on Taylor series, matching the recurring confusions raised in r/learnmath and r/calculus threads and the standard "People Also Ask" questions on the topic.

Dropping the factorial in the denominator.

Where it slips in:

A student writes the series as ∑f(n)(a)(x−a)n\sum f^{(n)}(a)(x-a)^n, forgetting to divide each derivative by n factorialn\text{ factorial}.

Don't do this:

Do not attach a raw derivative to a power. Without the factorial the coefficients are wrong from the second term onward.

The correct way:

Divide every derivative by its factorial: the nn-th coefficient is f(n)(a)n factorial\dfrac{f^{(n)}(a)}{n\text{ factorial}}. The factorial is exactly what cancels the number that differentiating (x−a)n(x-a)^n produces.

Confusing the Taylor polynomial with the Taylor series.

Where it slips in:

A student treats a two- or three-term approximation as if it were the exact function, or thinks the infinite series and a finite cut-off are the same object.

Don't do this:

Do not call a truncated sum "equal" to f(x)f(x). A finite Taylor polynomial is an approximation with a remainder Rn(x)R_n(x); only the full infinite series can equal the function.

The correct way:

Keep the two ideas separate: the polynomial Tn(x)T_n(x) is finite and approximate, the series is infinite and (where it converges) exact. Write the remainder term when accuracy matters.

Ignoring the interval of convergence.

Where it slips in:

A student uses the series for 11−x\dfrac{1}{1-x} or ln⁡(1+x)\ln(1+x) at a value of xx outside the range where it converges, and gets a nonsense answer.

Don't do this:

Do not assume a Taylor series equals its function for every xx. The geometric series ∑xn\sum x^n diverges once ∣x∣≥1\lvert x \rvert \ge 1, so the formula is simply false there.

The correct way:

Check the interval of convergence first. A series equals the function only where the remainder Rn(x)→0R_n(x) \to 0, which for 11−x\dfrac{1}{1-x} means ∣x∣<1\lvert x \rvert < 1.

Evaluating the derivatives at xx instead of at the centre aa.

Where it slips in:

A student leaves the derivatives as functions of xx inside the coefficients, instead of plugging in the centre.

Don't do this:

Do not write f(n)(x)n factorial(x−a)n\dfrac{f^{(n)}(x)}{n\text{ factorial}}(x-a)^n. The coefficients must be plain numbers, not functions.

The correct way:

Substitute x=ax = a into each derivative before dividing by the factorial, so every coefficient f(n)(a)n factorial\dfrac{f^{(n)}(a)}{n\text{ factorial}} is a constant.

Practice Problems On The Taylor Series

Work each one, then check against the answer that follows.

  1. Write the first three nonzero terms of the Maclaurin series of sin⁡x\sin x.
    (Answer: x−x36+x5120x - \dfrac{x^3}{6} + \dfrac{x^5}{120}.)

  2. Find the first four terms of the Maclaurin series of e2xe^{2x}.
    (Answer: 1+2x+2x2+4x33+⋯1 + 2x + 2x^2 + \dfrac{4x^3}{3} + \cdots, since f(n)(0)=2nf^{(n)}(0) = 2^n.)

  3. Use the first three terms of the cos⁡x\cos x series to approximate cos⁡(0.2)\cos(0.2) to 4 decimal places.
    (Answer: 1−0.02+0.00006‾≈0.98011 - 0.02 + 0.0000\overline{6} \approx 0.9801.)

  4. State the interval of convergence of the Maclaurin series of 11−x\dfrac{1}{1-x}.
    (Answer: −1<x<1-1 < x < 1, that is ∣x∣<1\lvert x \rvert < 1.)

  5. Find the first three terms of the Taylor series of 1x\dfrac{1}{x} centred at a=1a = 1.
    (Answer: 1−(x−1)+(x−1)2−⋯1 - (x-1) + (x-1)^2 - \cdots.)

  6. Using the exe^x series through the x2x^2 term, approximate e0.1e^{0.1}.
    (Answer: 1+0.1+0.005=1.10501 + 0.1 + 0.005 = 1.1050; the true value is 1.10521.1052.)

Where Should You Go Next After The Taylor Series?

The Taylor series sits at the meeting point of derivatives, sequences, and approximation, so several natural doors open from here.

  1. The derivative. Every Taylor coefficient is a derivative at the centre, so a firm grip on differentiation is what makes the whole construction routine.

  2. Sequences and series. A Taylor series is an infinite series, and the tests for when a series converges are what decide its interval of convergence.

  3. Differentiation of trigonometric functions. The cycling derivatives of sin⁡x\sin x and cos⁡x\cos x are exactly what generate their Maclaurin series. See the wider idea of calculus for where this fits.

If your child is meeting series for the first time, a live Bhanzu trainer teaches the Taylor series starting from the "why", the tangent line stretched into a curve, in the Bhanzu math program.

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Frequently Asked Questions

What is a Taylor series in simple terms?
A Taylor series rewrites a function as an endless sum of power terms, each built from one of the function's derivatives at a chosen centre aa. Keep a few terms and you get a polynomial that closely matches the function near that centre.
What is the difference between a Taylor series and a Maclaurin series?
None in method, only in centre. A Maclaurin series is a Taylor series with the centre fixed at a=0a = 0. The famous exe^x, sin⁡x\sin x, and cos⁡x\cos x expansions are Maclaurin series because centring at zero gives the simplest coefficients.
How is a Taylor series different from a Taylor polynomial?
A Taylor polynomial is a finite cut-off, the first few terms, and it approximates the function with a measurable error. A Taylor series is the full infinite sum, which equals the function wherever it converges. Confusing the two is the most common mistake on the topic.
Does a Taylor series always equal the original function?
No. It equals the function only where its remainder Rn(x)R_n(x) shrinks to zero, which defines an interval of convergence. The series for 11−x\dfrac{1}{1-x}, for example, equals the function only when ∣x∣<1\lvert x \rvert < 1 and is meaningless outside it.
Why is there a factorial in the Taylor series formula?
Differentiating (x−a)n(x-a)^n exactly nn times produces the factor n factorialn\text{ factorial}. Dividing by n factorialn\text{ factorial} in the coefficient cancels that factor, so the polynomial's nn-th derivative at the centre matches the function's exactly.
What is the Taylor series used for in real life?
The Taylor series lets computers evaluate functions with no finite formula, such as sin⁡x\sin x and exe^x, by adding a few polynomial terms. It also powers the small-angle approximation in physics, numerical solvers for differential equations, and gradient methods in machine learning.
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