Cheatsheet 04 - Differentiation

Mathematics for Master Students

The Derivative

The derivative of \(f\) at \(a\) is the instantaneous rate of change, the limit of the difference quotient:

\[f'(a) = \lim_{h \to 0} \frac{f(a + h) - f(a)}{h}\]

  • Geometric reading: the slope of the tangent line at \((a, f(a))\).
  • Business reading: how fast the output reacts to a tiny nudge at \(a\).
  • Sign of \(f'\) is a trend report: \(f' > 0\) increasing, \(f' < 0\) decreasing.
  • No derivative at kinks (e.g. \(|x|\) at \(0\)) or jumps: differentiable means a smooth graph.

Notation (all the same thing): \(\;f'(x) = \dfrac{df}{dx} = \dfrac{d}{dx}f(x)\).

Differentiation Rules

Building blocks. Memorize these:

\(f(x)\) \(f'(x)\) \(f(x)\) \(f'(x)\)
\(c\) \(0\) \(e^x\) \(e^x\)
\(x^n\) \(n x^{n-1}\) \(a^x\) \(a^x \ln a\)
\(\sqrt{x} = x^{1/2}\) \(\frac{1}{2\sqrt{x}}\) \(\ln x\) \(\frac{1}{x}\)

Combination rules. Decompose, then assemble:

Rule Formula
Constant multiple \((c f)' = c f'\)
Sum \((f + g)' = f' + g'\)
Product \((f g)' = f'g + f g'\)
Quotient \(\left(\dfrac{f}{g}\right)' = \dfrac{f'g - f g'}{g^2}\)
Chain \(\left(f(g(x))\right)' = f'(g(x)) \cdot g'(x)\)

The power rule takes every exponent. Rewrite negatives and roots as powers first:

  • \(\dfrac{1}{x} = x^{-1} \;\Rightarrow\; \left(\dfrac{1}{x}\right)' = -x^{-2} = -\dfrac{1}{x^2}\)
  • \(\sqrt{x} = x^{1/2} \;\Rightarrow\; \left(\sqrt{x}\right)' = \dfrac{1}{2}x^{-1/2} = \dfrac{1}{2\sqrt{x}}\)

Chain rule with \(e\) and \(\ln\): \(\;\left(e^{kx}\right)' = k\,e^{kx}\), and \(\;\left(\ln(g(x))\right)' = \dfrac{g'(x)}{g(x)}\).

TipName the Structure First

Before differentiating, ask: sum, product, quotient or chain? The right rule follows automatically. The chain rule’s inner derivative is not optional: \(\left((3x+1)^5\right)' = 5(3x+1)^4 \cdot 3\), never just \(5(3x+1)^4\).

Tangent Line

The tangent to \(f\) at \(x = a\) has slope \(f'(a)\) and passes through \((a, f(a))\):

\[y = f(a) + f'(a)(x - a)\]

A horizontal tangent (\(f'(a) = 0\)) marks a peak, a valley, or a flat spot, the starting point for optimization.

Second Derivative & Curvature

Differentiate twice: \(\;f''(x) = \left(f'\right)'(x) = \dfrac{d^2 f}{dx^2}\). While \(f'\) reports how fast \(f\) changes, \(f''\) reports how fast the slope changes.

Condition on an interval Shape Chord vs. graph
\(f''(x) \geq 0\) Convex (bends up) chord above
\(f''(x) \leq 0\) Concave (bends down) chord below
  • \(f(x) = x^2\): \(f'' = 2 > 0\), convex everywhere.
  • \(f(x) = \ln x\): \(f'' = -\frac{1}{x^2} < 0\), concave: diminishing returns.
  • Where \(f''\) changes sign, the bend switches: an inflection point.

Marginal Analysis

Marginal cost is \(C'(q)\), the instantaneous rate at which cost grows at output \(q\):

  • Practical reading: approximately the cost of one more unit (the \((q{+}1)\)-th).
  • Units: € per unit (a rate, not a total). \(C'(50) = 60\) means the 51st unit costs about €60, not that 50 units cost €60.
  • Marginal revenue \(R'(q)\): approximately the revenue from one more unit sold. Producing more pays off while \(R'(q) > C'(q)\).

Elasticity of Demand

For a demand function \(D(p)\), elasticity converts a unit rate into a percentage reaction:

\[\varepsilon = \frac{p}{D(p)} \cdot D'(p)\]

A 1% price increase changes demand by about \(\varepsilon\) percent. Demand falls in price, so \(\varepsilon < 0\).

\(|\varepsilon|\) Name Price increase → revenue
\(> 1\) elastic (overreacts) revenue falls
\(< 1\) inelastic (barely reacts) revenue rises
\(= 1\) unit elastic revenue at its peak

Common Pitfalls

WarningWatch Out
  • \((f \cdot g)' \neq f' \cdot g'\): use the product rule \(f'g + fg'\).
  • Chain rule: never forget the inner derivative. Multiply by the derivative of the inside.
  • Rewrite \(\frac{1}{x}\) and \(\sqrt{x}\) as powers before applying the power rule.
  • \(C'(q)\) is a rate in € per unit, not a total cost in €.
  • Elasticity is negative; classify by \(|\varepsilon|\) against \(1\).