Taylor's theorem with various forms of remainders
1. Taylor for About
If has continuous partials up to order near , then for :
where expands binomially, e.g. gives . This is the two-variable analogue of .
For , this becomes Maclaurin.
2. Remainder — Three Usual Forms
Let be some intermediate point .
- Lagrange form:
— useful for bounds (estimate max derivative on segment).
- Cauchy form:
— sometimes sharper.
- Peano / o-notation:
meaning remainder smaller than where — shows approximation order.
For exams, Lagrange suffices; mention others for completeness.
3. Linear and Quadratic Approximation (most used)
- First-order (tangent plane):
with error .
- Second-order: add — needed for maxima theory and error .
4. Worked Examples
(a) Expand f(x,y)= e^x cos y about (0,0) to second order:
f(0,0)=1, f_x= e^x cos y →1, f_y= -e^x sin y →0,
f_{xx}= e^x cos y→1, f_{xy}= -e^x sin y→0, f_{yy}= -e^x cos y→-1
⇒ f(h,k) ≈ 1 + h + (h² - k²)/2 + R3 ; i.e. e^x cos y ≈1 + x + (x² - y²)/2 ✓
Check: product of series e^x=1+x+x²/2, cos y=1-y²/2 confirms.
(b) Expand f(x,y)= sin(x+y) about (0,0) to third order: use single variable t=x+y
sin t = t - t³/6 +... ⇒ f ≈ (x+y) - (x+y)³/6 ✓
(c) Estimate error for √(1+x+y) about (0,0) linear: √(1+h+k)≈1+(h+k)/2 ; Lagrange remainder
= -(h+k)²/[8(1+θ(h+k))^{3/2}] ≤ (h+k)²/8 bounds ✓
(d) f(x,y)= log(1+x+y) : expansion log(1+t)=t -t²/2 +t³/3 ; t=x+y ⇒ log≈(x+y)-(x+y)²/2 ✓
5. Convergence and Use
Taylor's infinite series () converges where analytic (polynomials, , everywhere; for ). Remainder estimate tells you how many terms keep error < tolerance.
6. Exam Points
- State Taylor for about with Lagrange remainder — 5 marks, very frequent.
- Expand to second/third order about — 5-7 marks, very frequent.
- Estimate remainder / error bound — 3-5 marks.
- Second-order Taylor for maxima derivation (next topics) — 5 marks, frequent.