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How does the three-tiered number line model demonstrate the chain rule for the composite function g(h(x))=sin⁡(x2)g(h(x)) = \sin(x^2)?

The model tracks a small input change dxdx through successive local linear approximations. First, the inner function h(x)=x2h(x)=x^2 scales the input change by its derivative h′(x)=2xh'(x)=2x. Second, the outer function g(u)=sin⁡(u)g(u)=\sin(u) scales the resulting intermediate change by its derivative evaluated at the inner output, g′(h(x))=cos⁡(x2)g'(h(x))=\cos(x^2). The total change is the product of these two local scaling factors, yielding the derivative 2xcos⁡(x2)2x\cos(x^2).

Conditions

  • Functions hh and gg are differentiable at the relevant points.
  • The input change dxdx is infinitesimal.
  • The outer derivative is evaluated at the inner function's output h(x)h(x), not at xx.

Reasoning, step by step

  1. Start with an input xx and a small perturbation dxdx.
  2. Apply the inner function h(x)=x2h(x)=x^2; the change in output is approximately h′(x)dx=2xdxh'(x)dx = 2x dx.
  3. Pass this intermediate change to the outer function g(u)=sin⁡(u)g(u)=\sin(u).
  4. Evaluate the outer derivative at the current intermediate value u=h(x)=x2u=h(x)=x^2, giving g′(x2)=cos⁡(x2)g'(x^2)=\cos(x^2).
  5. Multiply the intermediate change by the outer scaling factor: cos⁡(x2)⋅(2xdx)\cos(x^2) \cdot (2x dx).
  6. Identify the total change as dy=2xcos⁡(x2)dxdy = 2x\cos(x^2)dx, so the derivative is 2xcos⁡(x2)2x\cos(x^2).

Example

Near x=1.5x=1.5, the inner rate is 2(1.5)=32(1.5)=3. A small positive dxdx increases x2x^2 by roughly 3dx3dx. The outer rate is cos⁡(1.52)=cos⁡(2.25)\cos(1.5^2)=\cos(2.25), which is negative. Thus, the final sine value decreases locally, and the overall derivative is 3cos⁡(2.25)3\cos(2.25).

Common misconceptions

  • Evaluating the outer derivative cos⁡(u)\cos(u) at the original input xx instead of at x2x^2.
  • Thinking the chain rule is just multiplying derivatives g′(x)h′(x)g'(x)h'(x) without substituting the inner function into the outer derivative.
  • Believing the number line model implies discrete jumps rather than local linear approximations.

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