Practical skills and data analysis
Readings, uncertainties and tables
In Paper 3 you take real measurements. Record raw readings to the precision of the instrument (a metre rule to mm, a micrometer to mm). Repeat readings and average them; the absolute uncertainty is about half the range. Table headings need the quantity and unit, like . Calculated values get the same number of significant figures as the least precise raw data, or one more.
≈ 35 minPlanning an investigation
Paper 5's planning question gives you a suggested relationship, such as , and asks for a full plan. Identify the independent variable (what you change), the dependent variable (what you measure) and the control variables (what you keep constant). Describe exactly how each is measured, with named instruments and a labelled diagram. Say what graph you'll plot to get a straight line, how to find constants from it, and include specific safety precautions and extra detail for reliability.
≈ 40 minAnalysis, error bars and evaluation
In Paper 5's analysis question, you calculate derived values (like , or ) with their uncertainties, plot them with error bars, then draw the best-fit line and a worst acceptable line that still passes through all error bars. The uncertainty in the gradient is the difference between their gradients; similarly for the intercept. Use these to find a constant with its uncertainty, and say whether the data support the hypothesis.
≈ 40 minErrors and uncertainties
Random errors scatter readings either side of the true value and are reduced by repeating and averaging. Systematic errors shift every reading the same way and aren't reduced by repeating. Precise readings agree with each other; accurate ones are close to the true value. When quantities are added or subtracted, add absolute uncertainties; when multiplied or divided, add percentage uncertainties; for a power, multiply the percentage by the power.
≈ 35 minGraphs and evaluation
A good graph has labelled axes with units, scales that use more than half the grid, plotted points marked clearly and a thin best-fit line with points balanced on both sides. For the gradient, use a large triangle covering at least half the line and read its corners from the line, not from data points. Compare the gradient and intercept with a theoretical equation to find constants. Evaluating means identifying the biggest sources of uncertainty and suggesting specific, practical improvements.
≈ 35 min