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Applied Mathematics · Ch 3 — Differentiation and Its Applications

Summary

Summary

This chapter developed the techniques of differentiation and applied them to business and geometric problems. Its key ideas and formulae are collected below.

Differentiation techniques

  1. An implicit function is one in which the dependent variable is not expressed explicitly in terms of the independent variable; it is differentiated by differentiating both sides with respect to xx (treating yy as a function of xx) and then solving for dydx\dfrac{dy}{dx}.
  2. For a parametric function y=f(t), x=g(t)y=f(t),\ x=g(t):

dydx=dy/dtdx/dt.\dfrac{dy}{dx}=\dfrac{dy/dt}{dx/dt}.

  1. Logarithmic differentiation is applied to functions of the type f(x)g(x)f(x)^{g(x)} (such as xxx^x): take the logarithm of both sides first, then differentiate.
  2. Second and higher order derivatives: the second-order derivative is ddx ⁣(dydx)=d2ydx2=y′′=f′′(x)\dfrac{d}{dx}\!\left(\dfrac{dy}{dx}\right)=\dfrac{d^2y}{dx^2}=y''=f''(x), and the third-order derivative is ddx ⁣(d2ydx2)=d3ydx3=y′′′=f′′′(x)\dfrac{d}{dx}\!\left(\dfrac{d^2y}{dx^2}\right)=\dfrac{d^3y}{dx^3}=y'''=f'''(x).

Business applications

  1. Cost function: C(x)=V(x)+kC(x)=V(x)+k, where V(x)V(x) is the variable cost and kk is the fixed cost.
  2. Revenue function: R(x)=p⋅xR(x)=p\cdot x, where pp is the price per unit and xx is the output (sales) at price pp.
  3. dydx\dfrac{dy}{dx} is the rate of change (instantaneous rate) of yy with respect to xx — the change in yy for a very small change in xx.
  4. Marginal cost and marginal revenue are the derivatives of the cost and revenue functions:

MC=C′(x)=dCdx,MR=R′(x)=dRdx.\text{MC}=C'(x)=\dfrac{dC}{dx},\qquad \text{MR}=R'(x)=\dfrac{dR}{dx}.

Tangents and normals

  1. The slope of the tangent to a curve at a point A(x0,y0)A(x_0,y_0) is dydx]A(x0,y0)\dfrac{dy}{dx}\Big]_{A(x_0,y_0)}.
  2. The slope of the normal at A(x0,y0)A(x_0,y_0) is −1dydx]A(x0,y0)\dfrac{-1}{\dfrac{dy}{dx}\big]_{A(x_0,y_0)}}.
  3. The equation of the tangent to the curve at A(x0,y0)A(x_0,y_0) is (y−y0)=dydx](x0,y0)(x−x0)(y-y_0)=\dfrac{dy}{dx}\Big]_{(x_0,y_0)}(x-x_0).
  4. The equation of the normal to the curve at A(x0,y0)A(x_0,y_0) is (y−y0)=−1dydx](x0,y0)(x−x0)(y-y_0)=\dfrac{-1}{\dfrac{dy}{dx}\big]_{(x_0,y_0)}}(x-x_0).

Increasing, decreasing and monotonic functions

  1. A real function y=f(x)y=f(x) is an increasing function on (a,b)(a,b) if f′(x)>0f'(x)>0 for all x∈(a,b)x\in(a,b).
  2. A real function y=f(x)y=f(x) is a decreasing function on (a,b)(a,b) if f′(x)<0f'(x)<0 for all x∈(a,b)x\in(a,b).
  3. A function that is either increasing or decreasing on its domain is termed a monotonic function.
  4. An interior point x0x_0 of the domain is a critical point if either f′(x0)=0f'(x_0)=0 or ff is not differentiable at x0x_0.

Maxima and minima

  1. If ff is defined on a domain DD, then f(c)f(c) is the absolute minimum value if f(x)≥f(c)f(x)\ge f(c) for all x∈Dx\in D, and the absolute maximum value if f(x)≤f(c)f(x)\le f(c) for all x∈Dx\in D; such a point cc is a point of extremum.
  2. First derivative test at a critical point cc: if f′f' changes sign from negative to positive as xx increases through cc, then cc is a point of local minimum; if it changes from positive to negative, cc is a point of local maximum; if f′f' does not change sign, cc is a point of inflexion. …