← Unit 3: Further calculus and statistics

QLDMath MethodsSyllabus dot point

Topic 1: Further differentiation and applications

Differentiate exponential and logarithmic functions, including compositions of the form $e^{f(x)}$ and $\ln(f(x))$, and apply the derivatives to model and analyse rates of change

A focused answer to the QCE Mathematical Methods Unit 3 dot point on differentiating exponential and logarithmic functions. Covers the derivatives of $e^x$, $a^x$, $\ln x$ and $\log_a x$, the chain rule generalisations $e^{f(x)}$ and $\ln(f(x))$, and the application to rates of change, with worked Paper 1 and Paper 2 examples.

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What this dot point is asking

QCAA wants you to differentiate exponential and logarithmic functions, including compositions like ef(x)e^{f(x)} and ln⁑(f(x))\ln(f(x)), and apply those derivatives to model rates of change in context. Exponential and logarithmic derivatives appear in Paper 1 (technology-free), in Paper 2 modelling questions, and in PSMTs that involve growth, decay, or any process where the rate is proportional to the current quantity.

The answer

The base case

The exponential function with base ee is its own derivative.

ddx(ex)=ex\frac{d}{dx}(e^x) = e^x

This is the defining property of ee and is the reason exe^x appears in every growth and decay model in Unit 3.

The natural logarithm is the inverse of exe^x and differentiates to the reciprocal.

ddx(ln⁑x)=1x,x>0\frac{d}{dx}(\ln x) = \frac{1}{x}, \quad x > 0

Chain-rule generalisations

For any differentiable inner function f(x)f(x):

ddx(ef(x))=fβ€²(x)ef(x)\frac{d}{dx}\bigl(e^{f(x)}\bigr) = f'(x) e^{f(x)}

ddx(ln⁑(f(x)))=fβ€²(x)f(x),f(x)>0\frac{d}{dx}\bigl(\ln(f(x))\bigr) = \frac{f'(x)}{f(x)}, \quad f(x) > 0

These two formulas cover almost every Methods question. Memorise them in this form.

Other bases

For a>0a > 0 and aβ‰ 1a \neq 1, use the change of base ax=exln⁑aa^x = e^{x \ln a}, which gives

ddx(ax)=(ln⁑a) ax.\frac{d}{dx}(a^x) = (\ln a) \, a^x.

Similarly, log⁑ax=ln⁑xln⁑a\log_a x = \dfrac{\ln x}{\ln a}, so

ddx(log⁑ax)=1xln⁑a.\frac{d}{dx}(\log_a x) = \frac{1}{x \ln a}.

QCAA frequently rewards students who recognise that axa^x is not differentiated by the power rule. The power rule applies to xnx^n (variable base, constant exponent), not axa^x (constant base, variable exponent).

Logarithm laws first

Before differentiating a complicated logarithm, simplify using logarithm laws. For example,

ln⁑(x2x+1)=2ln⁑x+12ln⁑(x+1),\ln\bigl(x^2 \sqrt{x + 1}\bigr) = 2 \ln x + \frac{1}{2} \ln(x + 1),

which differentiates to 2x+12(x+1)\dfrac{2}{x} + \dfrac{1}{2(x + 1)} in one step, with no quotient rule needed.

Worked examples

Direct chain rule

Differentiate y=eβˆ’2xy = e^{-2x}.

Let f(x)=βˆ’2xf(x) = -2x, so fβ€²(x)=βˆ’2f'(x) = -2. Then dydx=βˆ’2eβˆ’2x\dfrac{dy}{dx} = -2 e^{-2x}.

Logarithm of a polynomial

Differentiate y=ln⁑(x2+4)y = \ln(x^2 + 4).

dydx=2xx2+4\dfrac{dy}{dx} = \dfrac{2x}{x^2 + 4}.

Non-ee exponential

Differentiate y=5xy = 5^x.

dydx=(ln⁑5)β‹…5xβ‰ˆ1.6094β‹…5x\dfrac{dy}{dx} = (\ln 5) \cdot 5^x \approx 1.6094 \cdot 5^x.

Logarithm laws save work

Differentiate y=ln⁑ ⁣(x3x2+1)y = \ln\!\left( \dfrac{x^3}{x^2 + 1} \right).

Rewrite first: y=3ln⁑xβˆ’ln⁑(x2+1)y = 3 \ln x - \ln(x^2 + 1).

dydx=3xβˆ’2xx2+1\dfrac{dy}{dx} = \dfrac{3}{x} - \dfrac{2x}{x^2 + 1}.

Modelling context

A quantity decays according to Q(t)=200eβˆ’0.05tQ(t) = 200 e^{-0.05 t} milligrams, with tt in days. The rate of decay at t=10t = 10 is

Qβ€²(t)=βˆ’10eβˆ’0.05t,Qβ€²(10)=βˆ’10eβˆ’0.5β‰ˆβˆ’6.07Β mg/day.Q'(t) = -10 e^{-0.05 t}, \quad Q'(10) = -10 e^{-0.5} \approx -6.07 \text{ mg/day}.

The negative sign confirms decay; the magnitude is the current rate of loss.

Common traps

Treating axa^x like xnx^n. ddx(3x)β‰ xβ‹…3xβˆ’1\frac{d}{dx}(3^x) \neq x \cdot 3^{x-1}. The correct answer is (ln⁑3)β‹…3x(\ln 3) \cdot 3^x.

Forgetting the chain rule factor. ddx(e2x)=2e2x\frac{d}{dx}(e^{2x}) = 2 e^{2x}, not e2xe^{2x}. The factor of 22 comes from fβ€²(x)=2f'(x) = 2.

Missing the domain on ln⁑x\ln x. The natural log is only defined for x>0x > 0. If a domain crosses zero, you may need ln⁑∣x∣\ln|x| instead. In Paper 1, state the domain when QCAA asks for it.

Skipping logarithm laws. Differentiating ln⁑(uv)\ln(uv) directly with the chain rule still works but is slower and more error-prone than splitting first to ln⁑u+ln⁑v\ln u + \ln v.

Forgetting the sign in decay. A decay model Q(t)=Aeβˆ’ktQ(t) = A e^{-kt} with k>0k > 0 has derivative βˆ’kAeβˆ’kt-k A e^{-kt}, which is negative. The negative sign carries through and is part of the answer.

In one sentence

The exponential function exe^x is its own derivative and the natural log differentiates to 1x\frac{1}{x}, and applying the chain rule turns these into ddxef(x)=fβ€²(x)ef(x)\frac{d}{dx} e^{f(x)} = f'(x) e^{f(x)} and ddxln⁑(f(x))=fβ€²(x)f(x)\frac{d}{dx} \ln(f(x)) = \frac{f'(x)}{f(x)}, with non-ee bases handled by writing ax=exln⁑aa^x = e^{x \ln a}.

Past exam questions, worked

Real questions from past QCAA papers on this dot point, with our answer explainer.

2023 QCAA-style P13 marksDifferentiate $y = e^{3x^2 + 2}$ with respect to $x$.
Show worked answer β†’

This is a composition, so use the chain rule generalisation ddxef(x)=fβ€²(x)ef(x)\frac{d}{dx} e^{f(x)} = f'(x) e^{f(x)}.

Let f(x)=3x2+2f(x) = 3x^2 + 2, so fβ€²(x)=6xf'(x) = 6x.

dydx=6xβ‹…e3x2+2.\frac{dy}{dx} = 6x \cdot e^{3x^2 + 2}.

Markers reward explicit identification of f(x)f(x) and fβ€²(x)f'(x), application of the rule, and a tidy final answer with the exponential factor on the right.

2022 QCAA-style P24 marksA population of bacteria is modelled by $N(t) = 500 e^{0.15 t}$ where $t$ is hours after measurement. (a) Find the rate of change of the population at $t = 6$ hours. (b) Interpret this rate in context.
Show worked answer β†’

A 4-mark answer needs the derivative, the substituted value, and a contextual interpretation.

(a) Nβ€²(t)=500β‹…0.15β‹…e0.15t=75e0.15tN'(t) = 500 \cdot 0.15 \cdot e^{0.15 t} = 75 e^{0.15 t}.

At t=6t = 6: Nβ€²(6)=75e0.9β‰ˆ75Γ—2.4596β‰ˆ184.5N'(6) = 75 e^{0.9} \approx 75 \times 2.4596 \approx 184.5 bacteria per hour.

(b) Six hours after measurement, the population is growing at about 184 bacteria per hour. Because the model is exponential, the rate of growth itself increases with time; this rate would be roughly 220 per hour an hour later.

Markers reward the chain-rule derivative, an accurate numerical value (3 significant figures is fine on Paper 2), and a sentence interpreting the rate in context with correct units.

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