This comprehensive Pearson Edexcel IAL Physics Unit 6 (WPH16/01) Master Revision Guide covers Practical Skills in Physics II – the A2 practical skills paper. Aligned with the 2019–2025 exam series and based on Principal Examiner Reports (2019–2024).

What’s inside?

Skills heatmap – Critical skills appear every sitting: % uncertainty calculation (Δx/x × 100), combining uncertainties (add % for ×/÷, multiply by n for powers), graph plotting (scale ≥½ grid, crosses ×, best-fit line), gradient calculation (points ON the line, units stated), linearisation (y = mx + c form), max/min gradient method (uncertainty = (m_max – m_min)/2), error identification (systematic vs random, direction of effect), specific improvements, and planning answers (5-component framework).

Top 15 penalised errors – Gradient from data points (not line), units missing from gradient, % uncertainty formula inverted, vague improvements (“use better equipment”), no units in table headers, best-fit forced through origin, precision vs accuracy confused, and max/min lines through extreme points only.

Linearisation reference – All Unit 4 and Unit 5 contexts: SHM (T² vs m, gradient = 4π²/k), capacitor discharge (ln(V) vs t, gradient = –1/RC), radioactive decay (ln(N) vs t, gradient = –λ), Boyle’s law (p vs 1/V), resistivity (R vs L), Hubble’s law (v vs d), and attenuation (ln(I) vs x, gradient = –μ).

Mathematical skills – % uncertainty, combining rules (addition/subtraction: add absolute uncertainties; multiplication/division: add % uncertainties; powers: multiply % by n), half-range method for repeats, uncertainty in gradient (max/min lines), and identifying largest uncertainty contributor.

Model answers – Graph planning (T² vs m, gradient = 4π²/k), gradient calculation (points on line, units), % uncertainty (half-range method), error evaluation (name → direction → improvement).

Exam predictions – High-confidence: linearisation (SHM/capacitor/decay), full graph plotting (4–6 marks), % uncertainty calculation, error identification with direction and improvement, and uncertainty in gradient (max/min method).

Teacher tools – Diagnostic activities (graph plotting, linearisation, % uncertainty), structured practical tasks (graph relay, uncertainty race, linearisation card sort), differentiated revision (support/core/stretch), and classroom starters/exit tickets.

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