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A Level · Cambridge (CIE) · 9709

Interpret principal inverse trigonometric values

Read inverse notation as a function value, distinguish it from a reciprocal and explain why it gives only one selected angle.

Section 1.5 · Trigonometry

Pure Mathematics 1 · Trigonometry · 1.5

Pure Mathematics 1 (Paper 1) · AS & A Level Mathematics 9709, 2026–2027. State angle units and find every solution in the supplied interval; general forms of solution are not required in section 1.5. Written practice is self-checked.

Before you begin

  • Understand a one-to-one function and an inverse.
  • Know the signs and exact values of basic trigonometric ratios.

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

Quick readiness check

Can a real sin⁻¹(1.2) be evaluated?

What you will learn

  • Use sin⁻¹, cos⁻¹ and tan⁻¹ to denote principal inverse values.
  • State their principal ranges and distinguish one inverse value from all solutions of an equation.

Restrict the original function to make an inverse

Sine, cosine and tangent repeat, so an unrestricted ratio cannot identify a unique input angle. Principal inverse values choose branches where the original function is one-to-one. In radians, sin⁻¹ has output range [−π/2, π/2], cos⁻¹ has [0, π], and tan⁻¹ has (−π/2, π/2). The degree equivalents are [−90°, 90°], [0°, 180°] and (−90°, 90°).

Real sin⁻¹ and cos⁻¹ accept inputs only in [−1, 1]; tan⁻¹ accepts every real input. For example sin⁻¹(−√3/2) = −π/3, cos⁻¹(−1/2) = 2π/3 and tan⁻¹(−1) = −π/4. Select calculator mode for the intended angle unit, and do not treat an out-of-range sine input as a calculator fault.

The superscript −1 denotes an inverse, not a reciprocal

sin⁻¹(1/2) is the principal angle π/6; 1/sin(π/6) is the reciprocal number 2. They are different operations with different inputs and outputs. Likewise, sin⁻¹(sin 150°) = 30°, because 150° is outside sine's principal inverse range. Inverting an output recovers the original input only when that input belongs to the selected branch.

If sin θ = 1/2 for 0° ≤ θ ≤ 180°, the inverse key gives 30° but the graph also gives 150°. The inverse function returns one principal value; solving the equation requires every value in the supplied interval. Here the principal branches are the useful ideas; specialised inverse-function identities are outside this introductory section.

Pause and explain

What does sin⁻¹(1/2) return in degrees?

Put the idea to work

Worked example

Find sin⁻¹(−√3/2), cos⁻¹(−1/2) and tan⁻¹(−1) in radians.

Show the worked solution
  1. The sine inverse range is [−π/2, π/2], so choose −π/3.
  2. The cosine inverse range is [0, π], so choose 2π/3.
  3. The tangent inverse range is (−π/2, π/2), so choose −π/4; each selected angle produces the supplied ratio.

Answer −π/3, 2π/3 and −π/4 respectively.

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

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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

Evaluate sin⁻¹(1/2) and cos⁻¹(1/2) exactly in radians.

Give me a hint

Both use the ratio 1/2, but their functions and principal branches differ.

Compare my reasoning
  1. Within sine's principal interval, sin(π/6) = 1/2.
  2. Within cosine's principal interval, cos(π/3) = 1/2.
  3. Both values belong to their appropriate output ranges and can be checked in the original functions.

sin⁻¹(1/2) = π/6; cos⁻¹(1/2) = π/3.

Look for these in your work

  • Choose the original function's special angle.
  • Check the principal interval and retain exact radian form.
2 · Independent

Evaluate cos⁻¹(−√2/2) and sin⁻¹(−√2/2) in degrees.

Give me a hint

Use the 45° reference angle but choose a value in each inverse's own output range.

Compare my reasoning
  1. For cosine, choose the quadrant-II angle 135° within [0°, 180°].
  2. For sine, choose −45° within [−90°, 90°].
  3. The same ratio does not require the same principal angle; substitution verifies both.

cos⁻¹(−√2/2) = 135°; sin⁻¹(−√2/2) = −45°.

Look for these in your work

  • Use different principal ranges for sine and cosine.
  • Verify the sign of the ratio at each selected angle.
3 · Transfer

A sensor gives sin θ = 1/2 with 0° ≤ θ ≤ 180°. A learner records only θ = sin⁻¹(1/2) = 30°. Explain and complete the answer.

Give me a hint

The supplied angle interval is wider than the branch chosen by the inverse key.

Compare my reasoning
  1. The inverse key correctly returns the principal value 30°.
  2. Sine is also positive with the same magnitude at 180° − 30° = 150°.
  3. Both angles lie in the sensor's interval and give 1/2; no other angle there does.

θ = 30° or 150°; the principal inverse alone misses the second permitted angle.

Look for these in your work

  • Distinguish a correct principal value from a complete solution set.
  • Use the given physical interval to retain both possible angles.

Common mistakes

  • Inverse notation does not mean the reciprocal of a trigonometric value.
  • The inverse key returns one principal angle, rather than every equation solution.
  • Sine and cosine inverse inputs must be between −1 and 1.
Recall without your notes

What can you explain now?

Evaluate sin⁻¹(sin 150°) in degrees and explain the result.

Compare with the explanation

30°, because sine's principal inverse range is [−90°, 90°].

sin 150° = 1/2, whose principal sine inverse is 30°, not the original angle outside that branch.

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

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Make it stick

State each inverse's input and principal output ranges. Give an example where applying sin⁻¹ to a sine value does not recover the original angle.

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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