Calculus I · Building a Function From Its Derivatives

Match the curvature: the quadratic approximation

Bending is what the second derivative measures. So let’s look for a parabola that matches ff not in two ways but in three — value, slope, and curvature at aa. Write the unknown parabola in powers of (x−a)(x-a), which makes everything easy to evaluate at aa:

P(x)=c0+c1(x−a)+c2(x−a)2.P(x) = c_0 + c_1(x-a) + c_2(x-a)^2.

Now force the three matches, computing each derivative and plugging in x=ax = a (where every (x−a)(x-a) becomes 00):

  • Value: P(a)=c0P(a) = c_0, so matching f(a)f(a) forces c0=f(a)c_0 = f(a).
  • Slope: P′(x)=c1+2c2(x−a)P'(x) = c_1 + 2c_2(x-a), so P′(a)=c1P'(a) = c_1, forcing c1=f′(a)c_1 = f'(a).
  • Curvature: P″(x)=2c2P''(x) = 2c_2, so P″(a)=2c2P''(a) = 2c_2, forcing c2=f″(a)2c_2 = \dfrac{f''(a)}{2}.

So the best quadratic is

P(x)=f(a)+f′(a)(x−a)+f″(a)2(x−a)2.P(x) = f(a) + f'(a)(x-a) + \frac{f''(a)}{2}(x-a)^2.

It contains the tangent line (the first two terms) and adds one bending term. It hugs the curve better, and over a wider window. (Figure 7.2: the same curve with its tangent and its matching parabola; the parabola tracks the curve far past where the line gave up.)

Figure 7.2 The pattern is already visible — keep matching higher derivatives, keep adding terms — so let’s find the general rule, and the factorial it hides.


The general pattern, and why the factorial is forced

Suppose we want a degree-nn polynomial matching ff and its first nn derivatives at aa:

P(x)=∑k=0nck(x−a)k.P(x) = \sum_{k=0}^{n} c_k\,(x-a)^k.

To find ckc_k, differentiate PP exactly kk times and evaluate at aa. The key is what happens to a single power (x−a)j(x-a)^j when you hit it with kk derivatives:

  • If j<kj < k: you differentiate it down to a constant and then past it — it becomes 00.
  • If j>kj > k: after kk derivatives it still carries a factor of (x−a)(x-a), which is 00 at x=ax = a.
  • If j=kj = k: differentiating (x−a)k(x-a)^k exactly kk times peels off k,k−1,…,1k, k-1, \ldots, 1 in turn, leaving the constant k!=k⋅(k−1)⋯2⋅1k! = k\cdot(k-1)\cdots 2\cdot 1.

So when you compute P(k)(a)P^{(k)}(a), every term dies except the kk-th, which leaves ck⋅k!c_k \cdot k!. Setting that equal to f(k)(a)f^{(k)}(a):

P(k)(a)=ckk!=f(k)(a)⇒ck=f(k)(a)k!P^{(k)}(a) = c_k\,k! = f^{(k)}(a) \qquad\Longrightarrow\qquad \boxed{\;c_k = \frac{f^{(k)}(a)}{k!}\;}

There’s your factorial, and now you know why it’s there: it’s the k!k! that falls out of differentiating (x−a)k(x-a)^k down to the ground. We give the result a name.

The Taylor polynomial of degree nn for ff centered at aa is Tn(x)=∑k=0nf(k)(a)k!(x−a)k=f(a)+f′(a)(x−a)+f″(a)2!(x−a)2+⋯+f(n)(a)n!(x−a)n.T_n(x) = \sum_{k=0}^{n}\frac{f^{(k)}(a)}{k!}(x-a)^k = f(a) + f'(a)(x-a) + \frac{f''(a)}{2!}(x-a)^2 + \cdots + \frac{f^{(n)}(a)}{n!}(x-a)^n. Centered at a=0a = 0 it’s often called a Maclaurin polynomial. Let n→∞n\to\infty and (where it’s valid — see the remainder, below) you get the Taylor series.

Toolkit: Building a Taylor polynomial

  1. Compute f(a),f′(a),f″(a),…,f(n)(a)f(a), f'(a), f''(a), \ldots, f^{(n)}(a) — the derivatives at the center.
  2. Divide the kk-th one by k!k!.
  3. Assemble: ∑kf(k)(a)k!(x−a)k\sum_k \frac{f^{(k)}(a)}{k!}(x-a)^k. Look for a pattern in the coefficients — the best functions have one.

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