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A Level · Cambridge (CIE) · 9709

Solve modulus inequalities using intervals and valid sign cases

Translate a distance bound into an inside or outside interval and split a variable comparison where its inner expression changes sign.

Section 3.1 · Algebra

Pure Mathematics 2 & 3 · Shared Algebra foundations · 2.1 / 3.1
Exam scope and assessment notes

Pure Mathematics 2 (Paper 2, AS only) and Pure Mathematics 3 (Paper 3, A Level) · Shared Algebra foundations, Mathematics 9709, 2026–2027. Paper 1 knowledge is assumed. These modulus and polynomial requirements occur in both sections 2.1 and 3.1. Paper 3 additionally requires partial fractions and rational-power binomial expansions; follow its separate lessons for those methods. The AS route using Papers 1 + 2 cannot be carried forward to A Level. Both sections use linear modulus graphs; nonlinear y = |f(x)| and y = f(|x|) graphs are excluded. Polynomial dividends have degree at most 4 and divisors are linear or quadratic. Written practice is self-checked.

Before you begin

  • Solve linear inequalities and distinguish strict from inclusive endpoints.
  • Interpret the two branches of a linear modulus.

Work on paper. Try each question before revealing help, and explain why your method works.

Quick readiness check

Which interval represents |x − 2| < 3?

What you will learn

  • Solve strict and inclusive modulus bounds with correct endpoint treatment.
  • Solve an inequality with a variable comparison by intersecting each result with its sign-case interval.
Distance less than 3 from centre 2|3x − 6| < 9 ⇔ |x − 2| < 3-2-101234563 units3 units−1 < x < 5 · Open endpoints
The strict inequality |3x − 6| < 9 is equivalent to |x − 2| < 3, meaning a distance less than 3 from the centre 2. The blue interval is −1 < x < 5. Both boundary circles are open because at x = −1 or 5 the original modulus equals 9, which fails the strict comparison. The centre is included. This is an inside interval, rather than the two outside intervals for a greater-than distance condition.

A distance bound gives an inside or outside interval

For b > 0, |x − a| < b means a − b < x < a + b: the input is less than b units from a. With ≤, include both endpoints. By contrast |x − a| > b means x < a − b or x > a + b; the two outside intervals are joined by ‘or’, not ‘and’. With ≥, include the endpoints. A positive coefficient can first be factored out as a scale on the distance.

For |3x − 6| < 9, divide the modulus scale by 3 to get |x − 2| < 3, so −1 < x < 5. The endpoints are excluded because equality gives exactly 9. A non-positive bound needs separate care: |u| < 0 has no solutions, |u| ≤ 0 requires u = 0, and |u| ≥ 0 holds for all real u where the expression is defined. Do not apply a positive-distance interval rule to a negative bound.

Intersect each branch with the interval where it applies

For 2x + 5 < |x + 1|, split at x = −1. When x ≥ −1, the right side is x + 1, so the inequality gives x < −4, which has no overlap with that branch interval. When x < −1, the right side is −x − 1, so 3x < −6 gives x < −2, entirely within its branch. The complete solution is x < −2, with the boundary excluded.

Squaring an inequality is order-preserving only under suitable non-negative sign conditions. Here the left side is negative for some valid inputs, so squaring both sides blindly can discard solutions. Keep the original comparison, solve each linear branch and combine the valid intersections. Verify a sample from each reported interval and test boundary equality to decide whether endpoints belong.

Pause and explain

For the branch x ≥ −1 in 2x + 5 < |x + 1|, solving gives x < −4. What remains?

Put the idea to work

Worked example

Solve 2x + 5 < |x + 1| over the reals.

Show the worked solution
  1. For x ≥ −1, use |x + 1| = x + 1: the resulting x < −4 has no overlap with x ≥ −1.
  2. For x < −1, use |x + 1| = −x − 1: the inequality gives x < −2, valid in this branch.
  3. At x = −2 both sides equal 1, so the strict comparison excludes the boundary; combine to get x < −2.

Answer x < −2.

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From guided practice to a new situation

Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.

1 · Guided

Solve |3x − 6| < 9 and mark the boundary inputs on a number line.

Give me a hint

Use −9 < 3x − 6 < 9 and divide the full compound inequality by positive 3.

Compare my reasoning
  1. Add 6 to get −3 < 3x < 15.
  2. Divide by 3 to get −1 < x < 5.
  3. Use open endpoints at −1 and 5 because both give modulus 9 rather than a value below 9.

−1 < x < 5; both endpoints excluded.

Look for these in your work

  • Apply each operation to all three parts of the inequality.
  • Use open endpoints for the strict comparison.
2 · Independent

Solve |2x + 1| ≥ 5, stating whether each endpoint is included.

Give me a hint

The two signed cases are 2x + 1 ≤ −5 or 2x + 1 ≥ 5.

Compare my reasoning
  1. The negative branch gives 2x ≤ −6, so x ≤ −3.
  2. The positive branch gives 2x ≥ 4, so x ≥ 2.
  3. Combine with ‘or’; both endpoints give modulus 5 and are included.

x ≤ −3 or x ≥ 2; both endpoints included.

Look for these in your work

  • Use two outside intervals joined by ‘or’.
  • Retain equality at both boundary values.
3 · Transfer

For d(t) = 3t − 12 metres on 0 ≤ t ≤ 6 seconds, find the full time interval when the reference distance |d(t)| is at most 3 m.

Give me a hint

An ‘at most’ distance bound is inclusive; intersect its interval with the stated time domain.

Compare my reasoning
  1. Use −3 ≤ 3t − 12 ≤ 3.
  2. Adding 12 and dividing by 3 gives 3 ≤ t ≤ 5.
  3. This interval lies within [0, 6]; both endpoint distances equal 3 m, so both times are included.

3 ≤ t ≤ 5 seconds, with both endpoints included.

Look for these in your work

  • Use an inclusive inside-distance interval.
  • Check both boundary values and the allowed time domain.

Common mistakes

  • Use ‘or’ for two outside intervals, not an impossible ‘and’ condition.
  • Intersect a branch solution with the interval where that branch is valid.
  • Keep strict endpoints open and do not square a signed comparison without justification.
Recall without your notes

What can you explain now?

Solve |x − 2| > 3.

Compare with the explanation

x < −1 or x > 5.

The input must lie more than 3 units from 2, so use the two outside intervals with strict endpoints.

After trying it yourself, choose your next review. This is your self-assessment.

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Make it stick

Contrast inside and outside modulus intervals, then explain why a sign-case answer must be intersected with its branch condition.

If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.

Keep learning Mathematics

Course scope and assessment

312 sequenced lessons provide 936 guided, independent and application problems covering the 160 objectives in sections 1.1–1.8, 2.1–2.6, 3.1–3.9, 4.1–4.5, 5.1–5.5 and 6.1–6.5. The map lists all 38 sections across six alternative components; all eight Pure Mathematics 1 sections and all six Pure Mathematics 2 sections, from Paper 2 Algebra through Numerical solution of equations, currently have full teaching sequences. Paper 3 Algebra, section 3.1, links the six shared foundation lessons plus six lessons on partial fractions and rational binomial expansions; Paper 3 logarithms, trigonometry and numerical equations use the shared lessons, with the Paper 1 graph foundation linked into trigonometry. Paper 3 differentiation combines the shared methods with its inverse-tangent derivative lesson. Paper 3 Integration links four shared standard and identity lessons plus seven advanced lessons, covering all six section 3.5 requirements. Eight Vectors lessons cover all six section 3.7 requirements, with 2D and 3D line and solid applications. Nine Differential equations lessons cover all four section 3.8 requirements, including Paper 3 integration techniques, initial conditions, equilibrium solutions and conditional model interpretations. Eleven Complex numbers lessons cover all eight section 3.9 requirements, with seven Argand diagrams and explicit argument and boundary checks. All nine Pure Mathematics 3 sections now have teaching linked to every mapped requirement. Nine Forces and equilibrium lessons cover all seven section 4.1 requirements, with six force diagrams, signed incline-friction intervals, reaction-dependent pull and push limits and separate-body third-law checks. Nine Kinematics lessons cover the four official section 4.2 requirements, with the graph requirement mapped to three relationships. Six motion diagrams support directed quantities, graph slopes and signed areas, Paper 1 time-calculus methods, reversal distances, constant-acceleration stages and shared-clock particle meetings. Six Momentum lessons cover both section 4.3 requirements, including signed system totals, conservation assumptions, outgoing velocities, coalescence, unknown masses and successive impacts. Four diagrams show system momentum through the stipulated events, and supplied kinetic-energy checks distinguish conservation of momentum from changes in kinetic energy. Twelve Newton’s laws lessons cover all four section 4.4 requirements, with vertical support and release stages, rough horizontal and incline motion, inferred parameters, hanging and surface pulley systems, rigid tow-bar thrust and slack-string transitions. Seven force diagrams support the separate-particle balances. Nine Energy, work and power lessons cover all five section 4.5 requirements, with angle-dependent work, kinetic and reference potential energy, signed net-work balances, smooth curved slides, rough and driven slopes, ideal connected-system energy and instantaneous power on hills. Five diagrams distinguish the energy inputs, losses and valid positive-speed force model. All five Mechanics sections now have teaching and staged practice linked to their mapped requirements. Thirteen Representation of data lessons cover all five section 5.1 requirements, including choice and limitations of displays, ordered and back-to-back stems, raw summaries and box plots, unequal-width density histograms, cumulative-frequency interpolation, descriptive moment calculations, grouped estimates, coding, combining two datasets and correcting totals. Six accessible diagrams retain repeated observations and distinguish numerical spread, frequency area and estimated readings. Ten Permutations and combinations lessons cover both official section 5.2 requirements, with selection and ordered roles, repeated objects, adjacency blocks, non-adjacency gaps, leading-zero cases, labelled multi-row seating and mixed restrictions. Six accessible diagrams show outcome trees, ordered versus unordered choices, repeated copies, blocks, gaps and distinct row seats. Eleven Probability lessons cover all four section 5.3 requirements, with equiprobable elementary outcomes, selection-based probabilities, complements and disjoint regions, independence tests, restricted sample spaces, two-way tables, replacement and removal trees, reversed conditions and unknown parameters. Seven accessible diagrams show dice outcomes, random subsets, event regions, a conditioned grid, a count table and two probability trees. Twelve Discrete random variables lessons cover all three official section 5.4 requirements, with complete probability tables, moment and parameter checks, binomial assumptions, exact probabilities and moments, geometric first-success probabilities, tails, expectation and integer reliability thresholds. Six accessible diagrams distinguish outcome grouping, weighted moments, fixed trials, discrete probability bars, waiting conventions and integer tail deadlines. Twelve Normal distribution lessons cover all three official section 5.5 requirements, with continuous-area interpretation, MF19 cumulative tables, full standardisation, tail and interval regions, conditional probabilities, percentiles, one- and two-parameter inference, binomial suitability, continuity corrections and approximate integer thresholds. Seven accessible diagrams show model areas, table reading, aligned scales, intervals, quantiles, matched binomial and normal shapes and whole integer cells. All five Statistics 1 sections now have teaching and staged practice linked to their mapped requirements. Fourteen Poisson distribution lessons cover all five official section 6.1 requirements, with homogeneous event-count assumptions, exposure scaling, exact masses and tails, conditional count events, moments, parameter inference, probability duration targets, disjoint and overlapping windows, rare-count binomial approximations, matched normal approximations and continuity corrections. Nine accessible diagrams show event exposures, unit conversions, discrete bars, complete tail complements, population moments, shared windows, approximate count models and integer cells. Exact checks distinguish approximate and exact close-target decisions. Fourteen Linear combinations lessons cover the six listed results in official section 6.2, with affine moments, signed scales and constant cases, expectation without independence, independent squared variance contributions, fixed and random fees, independent copies versus reused values, affine normal events, independent normal sums and differences, weighted and conditional areas, coefficient inference, exact independent Poisson sums and overlapping exposure limits. Nine accessible diagrams distinguish scale changes, variance contributions, component costs, copy mechanisms, aligned normal scales, summed areas, Poisson count pairs and unsupported distribution claims. Fourteen Continuous random variables lessons cover both official section 6.3 requirements, with density validity and units, support-aware intervals, complements and conditional regions, first and second moments, percentiles by direct density areas, symmetry checks, parameter inference, infinite-support power and exponential integrals, divergent-moment limits and combined applications. Nine accessible diagrams distinguish density height from probability, normalisation, negative-density failures, central and conditional areas, mean versus median, percentile locations and partial infinite tails. Explicit cumulative distribution function knowledge is not required. Eighteen Sampling and estimation lessons cover all eight official section 6.4 requirements, with population and frame definitions, random-number selection, sampling-quality limits, independent sample-mean moments, normal means, CLT conditions, SE scaling, raw, summarised and coded unbiased estimates, known-variance and large-sample mean intervals, repeated-sampling interpretation, precision planning, proportion intervals, sparse-outcome limits and contextual applications. Ten accessible diagrams distinguish selection frames, number rejection, repeated sample means, population versus mean density, CLT models, variance divisors, interval targets, illustrative coverage, integer size checks and proportion margins. Eighteen Hypothesis tests lessons cover all five official section 6.5 requirements, with pre-specified alternatives, inclusive count tails, explicit equal-tail conventions, integer critical regions and actual significance, exposure-aware Poisson tests, continuity-corrected count approximations, normal and large-sample mean tests, confidence-interval connections, error classifications, fixed-region binomial, Poisson and normal error probabilities and sample-size power comparisons. Nine accessible diagrams show the testing procedure, exact count regions, unequal Poisson tails, discrete significance jumps, corrected count boundaries, matching mean intervals and alternative error distributions. All shared lessons are counted once in the course total. All 38 sections now link teaching and practice. Eight earlier overview lessons remain available, but do not count as full section coverage. This is a content-availability measure, not full programme completion or exam readiness. Written practice is self-checked, not officially marked. Check the 2028–2030 syllabus separately if sitting an examination from 2028; this teaching map uses 2026–2027 requirements.

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