Linear Approximations and Differentials: Fresh Take

  • Explain and use linearization to approximate a function’s value near a specific point
  • Calculate and interpret differentials to estimate small changes in function values
  • Measure the accuracy of approximations made with differentials by calculating relative and percentage errors

Linear Approximation of a Function at a Point

The Main Idea 

  • Linear approximation (or tangent line approximation) of [latex]f[/latex] at [latex]x=a[/latex] is given by:
    • [latex]L(x) = f(a) + f'(a)(x-a)[/latex]
  • Interpretation:
    • Uses the tangent line at a point to estimate function values nearby
    • Accurate for [latex]x[/latex] close to [latex]a[/latex]
    • Based on the idea that smooth functions look linear when zoomed in sufficiently
  • Key Formula:
    • [latex]f(x) \approx f(a) + f'(a)(x-a)[/latex] for [latex]x[/latex] near [latex]a[/latex]
  • Applications:
    • Estimating function values
    • Root approximation
    • Simplifying complex calculations
    • Basis for Newton’s method
  • Limitations:
    • Accuracy decreases as [latex]x[/latex] moves away from [latex]a[/latex]
    • Not suitable for functions with sharp turns or discontinuities at [latex]a[/latex]

Find the local linear approximation to [latex]f(x)=\sqrt[3]{x}[/latex] at [latex]x=8[/latex]. Use it to approximate [latex]\sqrt[3]{8.1}[/latex] to five decimal places.

Find the linear approximation for [latex]f(x)= \cos x[/latex] at [latex]x=\dfrac{\pi }{2}[/latex].

Find the linear approximation of [latex]f(x)=(1+x)^4[/latex] at [latex]x=0[/latex] without using the result from the preceding example.

Differentials and Amount of Error

The Main Idea 

  • For a function [latex]y = f(x)[/latex], the differential [latex]dy[/latex] is defined as: [latex]dy = f'(x) , dx[/latex]
    • [latex]dx[/latex] is an independent variable that can be any nonzero real number
  • Relationship to Linear Approximation:
    • [latex]\Delta y \approx dy[/latex] for small changes in [latex]x[/latex]
    • Based on the linear approximation: [latex]f(a + dx) \approx f(a) + f'(a) , dx[/latex]
  • Error Estimation:
    • Propagated Error: [latex]\Delta y = f(a + dx) - f(a)[/latex]
    • Estimated Error: [latex]\Delta y \approx dy \approx f'(a + dx) , dx[/latex]
  • Relative and Percentage Error:
    • Relative Error: [latex]\frac{\Delta q}{q}[/latex], where [latex]q[/latex] is the actual value
    • Percentage Error: Relative error expressed as a percentage
  • Applications:
    • Approximating function value changes
    • Estimating measurement errors in calculations
    • Analyzing accuracy in scientific measurements

For [latex]y=e^{x^2}[/latex], find [latex]dy[/latex].

For [latex]y=x^2+2x[/latex], find [latex]\Delta y[/latex] and [latex]dy[/latex] at [latex]x=3[/latex] if [latex]dx=0.2[/latex].

Estimate the error in the computed volume of a cube if the side length is measured to be 6 cm with an accuracy of 0.2 cm.