Revision Notes
OCR A Level Mathematics A: Laws of logarithms, exponential equations, linear form and modelling (H240) – Revision Notes
Condensed revision notes on log laws, exponential equations, log graphs and growth and decay models for OCR A Level Mathematics A, with a self-test.
- Subject
- Mathematics
- Level
- A LEVELS
- Topic
- Laws of logarithms, exponential equations, reduction to linear form and growth/decay modelling
- Author
- Marlbridge Academic Team
- Updated
Aligned to OCR A Level Mathematics (H240), Version 3.1 (August 2026), for first assessment in 2018. Official specification .
Syllabus page (what it covers and how it is assessed): OCR A Level Mathematics.
Syllabus points this page covers
H240
- 1.06 Exponentials and logarithms
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These revision notes condense sections 1.06f to 1.06i of the OCR A Level Mathematics A specification (Version 3.1, August 2026, for first assessment in 2018): laws of logarithms, exponential equations, reduction to linear form and exponential modelling. All four are listed as Stage 1, so they are common to AS and A Level. For full explanations and fully worked examples, read the study guide first.
Then test yourself with the practice questions. The course page is OCR A Level Mathematics, the printable list is the checklist, and the free diagnostics show which topics need work. The graphs of a^x, e^x and ln x and the gradient of e^kx are separate outcomes and are not covered here.
Key results
| Section | Result |
|---|---|
| 1.06f | log_a x + log_a y = log_a (xy) |
| 1.06f | log_a x − log_a y = log_a (x/y) |
| 1.06f | k log_a x = log_a (x^k), including k = −1 and k = −½ |
| 1.06f | log_a a = 1, log_a 1 = 0, ln e = 1, ln 1 = 0 |
| 1.06g | a^x = b gives x = ln b / ln a; e^x = b gives x = ln b |
| 1.06h | y = ax^n: plot lg y against lg x; gradient n, intercept lg a |
| 1.06h | y = kb^x: plot lg y (or ln y) against x; gradient lg b (or ln b), intercept lg k (or ln k) |
| 1.06i | N = N₀e^(kt): growth for k > 0, decay for k < 0; doubling or half-life time is ln 2 / |
Change of base is excluded from the laws outcome.
Laws of logarithms (1.06f)
Method: combining
- Put coefficients in as powers using the power law (k log x becomes log x^k).
- Add logs by multiplying, subtract logs by dividing.
- Check all logs share one base.
- Simplify, then use log_a a = 1 or log_a a^m = m if you need a number.
Reminder: 2 ln 3 + ln 4 − ln 6 = ln (9 × 4 / 6) = ln 6.
Method: solving log equations
- Combine into a single log on each side, or a single log equal to a number.
- Remove the logs: log_a f(x) = c means f(x) = a^c. If log f(x) = log g(x), then f(x) = g(x).
- Solve, then substitute back into every original logarithm.
- Reject any root that makes an input zero or negative.
Must-know distinctions
- log x + log y is log (xy), but log (x + y) cannot be split.
- log x / log y is not log (x/y), and it does not simplify to x/y.
- (log x)² is not 2 log x. The power law applies to the input of the log only.
- Reject a root only because of the domain, not because it is negative. A negative root is fine if every log input stays positive.
Exponential equations (1.06g)
Method: a^x = b
- Isolate the power so that a^x stands alone.
- Take ln of both sides (or logs to any one base).
- Bring the power down: x ln a = ln b.
- Divide: x = ln b / ln a. Round only at the end.
Method: x on both sides
Take logs, expand the brackets, collect the x terms on one side and factorise.
Reminder: 7^(2x−1) = 4^x
(2x − 1) ln 7 = x ln 4
x (2 ln 7 − ln 4) = ln 7
x = ln 7 / (2 ln 7 − ln 4) = 0.777 (3 s.f.)
Reminder: isolate first
4e^(−x) = 10 gives e^(−x) = 2.5, so −x = ln 2.5 and x = −ln 2.5 = −0.916 (3 s.f.).
Reminder: a hidden quadratic
e^(2x) − 7e^x + 12 = 0. Let t = e^x, so t² − 7t + 12 = 0 and (t − 3)(t − 4) = 0. Then e^x = 3 or e^x = 4, so x = ln 3 or x = ln 4. Both are valid because e^x is always positive. If a factor gives a negative or zero value for t, reject it.
Reduction to linear form (1.06h)
| Model | Take logs | Plot | Gradient | Intercept | Parameters |
|---|---|---|---|---|---|
| y = ax^n | lg y = n lg x + lg a | lg y against lg x | n | lg a | a = 10^(intercept) |
| y = kb^x | lg y = x lg b + lg k | lg y against x | lg b | lg k | b = 10^(gradient), k = 10^(intercept) |
| y = kb^x (natural logs) | ln y = x ln b + ln k | ln y against x | ln b | ln k | b = e^(gradient), k = e^(intercept) |
Method: from data to parameters
- Choose the model. A straight line on log-log axes means a power; a straight line with log y against x means exponential.
- Calculate the new columns (lg x and lg y, or x and ln y).
- Plot the points and draw a line of best fit by eye.
- Pick two points on the line, far apart, and find the gradient.
- Read or calculate the vertical intercept.
- Undo the log to get a or k, and undo it for the gradient if the model is exponential.
- Write the equation and quote values as estimates.
Reminder
A line of lg y against lg x with gradient 3 and intercept 0.6 gives n = 3 and a = 10^0.6 = 3.98, so y ≈ 3.98x³. The same sort of line for ln y against x with gradient 0.5 and intercept 2 gives b = e^0.5 = 1.65 and k = e² = 7.39.
Must-know distinctions
- The intercept on the vertical axis is the log of the constant, not the constant itself.
- On a log-log plot the gradient is the power n. On a log y against x plot the gradient is the log of the base b.
- Use the same base for every log in one question.
- Take points from the line, not from the data table, when you find the gradient.
Modelling with exponentials (1.06i)
Standard models
| Context | Model |
|---|---|
| Population growth | P = P₀e^(kt), k > 0 |
| Continuous compound interest | A = Pe^(rt) |
| Radioactive decay | m = m₀e^(−kt), k > 0 |
| Drug concentration | C = C₀e^(−kt), k > 0 |
Method: using a model
- Identify the initial value at t = 0.
- Use a second reading to find the rate constant k: e^(kt) = ratio, so k = ln (ratio) / t.
- To find a time, set the formula equal to the target, isolate the exponential and take ln.
- State the answer with units and the right degree of accuracy.
Reminder: C = 25e^(−0.3t). Time to fall to 5: e^(−0.3t) = 0.2, so t = ln 5 / 0.3 = 5.36. The half-life is ln 2 / 0.3 = 2.31.
Limitations and refinements
| Limitation | Possible refinement |
|---|---|
| Growth has no upper limit | A model that levels off at a maximum value |
| Decay goes to zero, but a background level exists | Add a constant to the model |
| Constant rate k may not hold for a long time | Let k change with time or conditions |
| Counts are whole numbers | Round answers sensibly, or note that the model is an approximation |
| Predictions far outside the data are uncertain | Collect more data, restrict the time range |
Always link the comment to the context. A statement like “the model is not accurate” is too vague to be a useful comment.
Quick self-test
- Evaluate log₅ 50 − log₅ 2.
- Write 3 log_a 2 + log_a 5 as one logarithm.
- Write −2 log_a x as a single logarithm.
- Solve 2^x = 50, giving x to 3 significant figures.
- Solve e^(2x) = 9, giving x as ln 3.
- Solve log₁₀ x + log₁₀ (x − 3) = 1.
- For y = 4x³, which axes make a straight line, and what are its gradient and intercept (in log base 10)?
- ln y against x is a straight line with gradient 0.5 and intercept 2. Write y in the form kb^x.
- A mass decays as m = m₀e^(−0.2t). Find the half-life to 3 significant figures.
- Give one limitation of the model P = P₀e^(kt) for a population.
Answers
- log₅ (50/2) = log₅ 25 = 2.
- log_a 8 + log_a 5 = log_a 40.
- log_a (1/x²).
- x = ln 50 / ln 2 = 5.64.
- e^(2x) = 9 gives 2x = ln 9 = 2 ln 3, so x = ln 3.
- x(x − 3) = 10, so x² − 3x − 10 = 0 and (x − 5)(x + 2) = 0. Reject −2 (log of a negative input). x = 5.
- lg y = 3 lg x + lg 4: lg y against lg x, gradient 3, intercept lg 4 = 0.602.
- b = e^0.5 and k = e², so y = 7.39 × 1.65^x.
- Half-life = ln 2 / 0.2 = 3.47.
- Any one of: growth is unbounded, so a real population would eventually run out of resources; k is assumed constant; the model gives non-integer counts.
Where marks are usually lost
- Splitting log (x + y) into two logs.
- Leaving a root that makes the input of a logarithm negative.
- Rounding in the middle of a calculation and losing accuracy in the final answer.
- Writing x = ln b × ln a instead of dividing, or dividing the wrong way round.
- Reading the vertical intercept of a log graph as a or k without undoing the log.
- Choosing points from the data table, not from the line of best fit, to find a gradient.
- Giving an exact answer when the question asks for 3 significant figures, or the reverse.
- Making a comment about a model that is generic (“it is not realistic”) with no link to the context.
Official syllabus
OCR, A Level Mathematics A (H240) specification, Version 3.1 (August 2026), for first assessment in 2018, published by OCR. These notes cover section 1.06f to 1.06i.
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