How do we differentiate exponential and logarithmic functions?
The derivative of e^x is itself, the derivative of ln x is 1/x, and the chain rule extends both to composite functions.
The derivatives of the exponential and natural log functions, the chain-rule extensions for composite exponentials and logarithms, and worked applications including growth models and stationary points.
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What this dot point is asking
The exponential function is special: it is its own derivative. The natural logarithm differentiates to . These two results, combined with the chain rule, let you differentiate every exponential and logarithmic model in Stage 2. They are also the reason the constant matters at all: is precisely the base for which the exponential curve has gradient exactly equal to its height at every point, which is why calculus is built around base rather than base or base .
The base results
Chain-rule extensions
When the exponent or the argument is itself a function of , multiply by its derivative:
Combining with the product and quotient rules
These derivatives frequently sit inside products and quotients.
Using the log laws to simplify first
Before differentiating a complicated log, expand it with the log laws - this is far easier than the quotient or product rule.
For , rewrite as , then
Common errors
Tangents to exponential and log curves
A common application is finding the equation of a tangent. The gradient at a point comes from the derivative, and the tangent line is then . For at , the gradient is and the point is , so the tangent is . For at , the gradient is and the point is , so the tangent is . These two tangents are reflections of each other in , which is the graphical echo of the exponential and logarithm being inverse functions.
Rates of change in models
Because , the derivative of an exponential model is proportional to the model itself. This is the defining feature of exponential growth and decay: the rate of change at any instant is a fixed multiple of the current amount. A positive gives growth and a negative gives decay. When SACE asks for the rate of growth of a population or the rate of cooling of an object, you differentiate the model and substitute the given time, exactly as in the worked population example above.
Why it matters
These derivatives are the basis of every exponential growth-and-decay and logarithmic application in Stage 2, and they connect directly to the antidifferentiation results in Topic 3 (since and are simply these rules reversed).
Exam-style practice questions
Practice questions written in the style of SACE Board exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
SACE 20232 marksCalculator-free. Find for . There is no need to simplify your answer.Show worked answer →
This is the exponential chain rule . The inner function is with .
So .
Marks: one for keeping the exponential factor , one for multiplying by . Writing alone and omitting the factor is the frequent error.
SACE 20222 marksCalculator-free. Find if .Show worked answer →
This is a product of and , so use the product rule .
Here and .
Marks: one for the product-rule set-up, one for the simplified derivative . Factoring is the form needed if the next part asks for stationary points.
SACE 20213 marksCalculator-assumed. For , find and hence the -coordinate of the stationary point.Show worked answer →
Use the log chain rule with , :
Stationary point where : the denominator is never zero, so , giving .
Marks: one for the chain-rule structure, one for on top, and one for solving to .
