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A Level · Cambridge (CIE) · 9709

Handle fixed positions and leading-zero restrictions

Choose the most restricted position first and divide digit problems into disjoint endpoint cases when branch sizes differ.

Statistics 1 · Permutations and combinations · 5.2
Exam scope and assessment notes

Probability & Statistics 1 (Paper 5, AS & A Level) · Mathematics 9709, 2026–2027, section 5.2. State whether order matters, objects are distinguishable, repetition is permitted and positions or rows are labelled. Count mutually exclusive cases before adding them; account for internal arrangements when using blocks. These lessons include seating in two or more rows. Arrangements in a circle are excluded from this syllabus section. Unless a question says otherwise, people and named roles are distinguishable, and selection is without replacement. Written practice is self-checked; human subject-teacher review remains pending.

Before you begin

  • Use the product rule without replacement.
  • Recognise even digits and the place value of a leading zero.

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

Quick readiness check

Which condition applies to a four-digit positive integer?

What you will learn

  • Count arrangements with fixed or restricted positions.
  • Separate integer leading-digit rules from code conventions.

A numeral and a code have different conventions

Using 0, 1, 2, 3 once each, there are 4! = 24 four-character codes. Four-digit positive integers cannot start with zero, so choose their first digit in three ways and arrange the remaining three digits in 3! ways: 18. Equivalently subtract the 3! = 6 codes that start with zero.

If a code is required to start with zero, zero is a fixed character, not an invalid leading digit. A four-character code from digits 0–5, with no repeated digit and initial zero, has 5 × 4 × 3 = 60 possibilities. Keep every position in the code; a leading zero is part of the recorded string.

Endpoint cases can have different branch sizes

For three-digit even integers from 0, 1, 2, 3, 4 without repetition, choose the final digit first. If it is 0, the leading digit has four choices and the middle digit three: 12 numbers. If it is 2 or 4, there are two final choices, three non-zero leading choices and three middle choices: 18 numbers. The total is 30.

A single product 3 × 4 × 3 is wrong here because the first-position count depends on whether zero was used at the end. Write disjoint cases and count each accurately. For fixed named objects in a row, remove their occupied positions before arranging the others; check that remaining restrictions still apply.

Pause and explain

Using 0, 1, 2, 3 once each, how many four-digit integers exist?

Put the idea to work

Worked example

Count four-digit integers using all of 0, 1, 2, 3 without repetition.

Show the worked solution
  1. The first digit is 1, 2 or 3, giving three choices.
  2. Arrange the three unused digits in the remaining three positions in 3! ways.
  3. The count is 3 × 6 = 18; zero is allowed in later positions.

Answer 18 integers.

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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

Count four-digit integers using 0, 1, 2, 3 exactly once each.

Give me a hint

There are three allowed first digits, then unrestricted remaining positions.

Compare my reasoning
  1. Choose the leading digit in three non-zero ways.
  2. Arrange the remaining three digits in 3! = 6 ways.
  3. Multiply 3 × 6 = 18.

18 integers.

Look for these in your work

  • Forbid zero only in the leading position.
  • Use every digit exactly once.
2 · Independent

Count three-digit even integers from 0, 1, 2, 3, 4 without repeated digits.

Give me a hint

Separate final digit zero from final digit two or four.

Compare my reasoning
  1. Final 0 gives 4 × 3 = 12 numbers.
  2. Final 2 or 4 gives 2 × 3 × 3 = 18 numbers, excluding zero from the leading position.
  3. These cases are disjoint, so total 12 + 18 = 30.

30 integers.

Look for these in your work

  • Apply the leading-zero restriction in both cases.
  • Explain why a single identical branch count would fail.
3 · Transfer

A four-character code uses digits 0–5 without repetition and must start with 0. Count codes and explain why the integer leading-zero rule does not exclude them.

Give me a hint

The first character is fixed; the other three are ordered unused digits.

Compare my reasoning
  1. Fix the initial zero in one way.
  2. Choose remaining characters in 5, 4 and 3 ways.
  3. The product is 60; a code records all four characters rather than integer digit length.

60 codes; their leading zero is a required character.

Look for these in your work

  • Retain the stated code convention.
  • Count the remaining ordered positions without replacement.

Common mistakes

  • A leading-zero prohibition belongs to an integer, not automatically to a code.
  • Choose restrictive positions before unrestricted ones.
  • Split cases when available choices depend on earlier decisions.
Recall without your notes

What can you explain now?

Is 0123 a four-character code or a four-digit integer?

Compare with the explanation

It can be a four-character code, but its numerical value is the three-digit integer 123.

The string length and integer place-value convention are different.

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

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Make it stick

Start with restricted positions; distinguish a digit string from an integer and add disjoint endpoint cases.

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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