Learn in your language
Skip to content
A Level · Cambridge (CIE) · 9709

Refine root brackets and justify the requested rounding

Retain the interval containing a root, narrow it with new sign checks and distinguish interval width from a rounding guarantee.

Section 2.6 · Numerical solution of equations

Pure Mathematics 2 & 3 · Numerical solution of equations · 2.6 / 3.6
Exam scope and assessment notes

Pure Mathematics 2 (Paper 2, AS only) and Pure Mathematics 3 (Paper 3, A Level) · Mathematics 9709, 2026–2027. Paper 1 graph and algebra knowledge is assumed. The AS route using Papers 1 + 2 cannot be carried forward to A Level. Shared sections 2.6 and 3.6 include locating roots graphically or by sign changes, notation for convergent approximation sequences, and using a given iteration or rearrangement to a prescribed accuracy. An iteration may fail to converge. Knowledge of the general condition for convergence is not required here. Check the original equation, domains and requested rounding. Written practice is self-checked.

Before you begin

  • Locate a root using valid sign changes.
  • Round decimal numbers and evaluate a function without premature rounding.

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

Quick readiness check

For opposite signs at a and b, how is midpoint refinement used?

What you will learn

  • Refine a continuous sign-change bracket, using midpoint tests or chosen decimal inputs.
  • Use an interval lying within one rounding band to justify an answer to prescribed decimal places.

Keep the half that retains the sign change

Once a continuous function has opposite signs at a and b, test the midpoint m = (a + b)/2. If f(m) = 0, you have found an exact root. Otherwise, keep whichever of [a, m] and [m, b] has opposite endpoint signs. Repeating this bracket-refinement method halves the interval width each time. The midpoint is a candidate approximation, not an exact root unless its original function value is zero.

For x² − 2 on [1, 2], midpoint 1.5 gives 0.25, so keep [1, 1.5]. Next midpoint 1.25 gives −0.4375, so keep [1.25, 1.5]. The new endpoint evidence preserves a root while narrowing its location. After n halvings the width is (b − a)/2ⁿ, and the midpoint's absolute error is at most half that width for a root within the bracket. This is a support method for reliable root location; use any particular iteration the question explicitly gives when requested.

Check a rounding band as well as a narrow width

To justify a rounded answer, make the entire root bracket lie inside the band that rounds to that answer. For the positive root of x² − 2, f(1.4142) = −0.00003836 and f(1.4143) = 0.00024449. The continuous sign change locates a root between them, and every input there rounds to 1.414 to three decimal places. Reporting 1.414 is a rounding claim; it does not mean f(1.414) equals zero.

A bracket narrower than 0.001 can still cross a three-decimal rounding boundary. For example, (1.4144, 1.4146) crosses 1.4145, so its width alone does not establish whether the rounded value is 1.414 or 1.415. Decimal places and significant figures are different instructions: 0.6823 rounds to 0.682 at three decimal places or three significant figures, but these notions do not always coincide for other-sized numbers. State the requested precision and retain extra digits during calculations.

Pause and explain

What extra check turns a narrow root bracket into a justified rounded answer?

Put the idea to work

Worked example

Use the bracket (1.4142, 1.4143) to justify the positive root of x² − 2 = 0 to three decimal places.

Show the worked solution
  1. Evaluate opposite signs −0.00003836 and 0.00024449 at the two endpoints.
  2. The polynomial is continuous, so a root lies strictly between those inputs.
  3. The whole bracket lies inside the rounding band [1.4135, 1.4145), so the root rounds to 1.414.

Answer Positive root approximately 1.414 to three decimal places, justified by the sign-change bracket.

Try a topic test

Choose Easy, Normal or Difficult. Save your answers and open worked review after finishing.

Test this topic →

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

For f(x) = x² − 2, start with [1, 2] and perform two midpoint refinements. Give the resulting bracket.

Give me a hint

Evaluate the midpoint sign and replace only the endpoint with the same sign.

Compare my reasoning
  1. The first midpoint 1.5 gives 0.25, so retain [1, 1.5].
  2. The second midpoint 1.25 gives −0.4375, so retain [1.25, 1.5].
  3. The two endpoint signs still differ and the final width is 1/4.

After two refinements: [1.25, 1.5], width 1/4.

Look for these in your work

  • Retain a valid continuous sign-change interval at both stages.
  • Use the new endpoints when calculating the next midpoint.
2 · Independent

A root of x³ − x − 1 lies between 1.3247 and 1.3248. Check the signs and report the root to three decimal places, explaining the rounding.

Give me a hint

Both endpoint values lie on the same side of the three-decimal rounding threshold 1.3245.

Compare my reasoning
  1. The function values are −0.000076579777 and 0.000349908992.
  2. Continuity locates a root inside this bracket.
  3. Every value in the bracket lies in [1.3245, 1.3255), giving rounded answer 1.325.

Root approximately 1.325 to three decimal places.

Look for these in your work

  • Verify the bracket using original polynomial values.
  • Use the entire rounding band rather than round just one trial input.
3 · Transfer

For a continuous function, suppose a root lies in (1.4144, 1.4146). A student reports 1.414 to three decimal places because the interval is less than 0.001 wide. Is that justified, and what further evidence is needed?

Give me a hint

Compare the bracket with the rounding threshold 1.4145.

Compare my reasoning
  1. The stated interval has width 0.0002 but crosses 1.4145.
  2. Some possible roots round to 1.414 and others to 1.415, so the report is not justified by this bracket alone.
  3. Refine with valid sign checks until the root bracket lies wholly within one rounding band, or establish an exact boundary root if that case occurs.

Not justified; refine the bracket to one side of 1.4145, or establish the exact boundary case.

Look for these in your work

  • Distinguish a width-based error statement from a rounding decision.
  • Specify evidence that actually resolves the requested precision.

Common mistakes

  • Retain opposite signs and the original function's domain at every refinement.
  • A midpoint is an approximation until checked as an exact root.
  • A narrow interval that crosses a rounding boundary does not settle the rounded answer.
Recall without your notes

What can you explain now?

Does a root bracket (1.4144, 1.4146) by itself establish a unique three-decimal rounded answer?

Compare with the explanation

No; it crosses the rounding boundary 1.4145.

Values on its two sides round differently even though the bracket is narrower than 0.001.

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

Your review choice appears on Today. Sign in to sync it across devices.

Make it stick

Refine a sign-change bracket twice. Explain how a midpoint error bound and a whole-band rounding check support different parts of a numerical answer.

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.

StudyForA · Learn with understanding

Original teaching content and links to official sources. Check your exam year and qualification before using a resource.