Science Practical Graph Skills: How to Draw Graphs That Score Full Marks

TL;DR
Graph drawing is tested in every science practical - Physics, Chemistry, and Biology - at both O-Level and A-Level. Most marks are lost not because of wrong data, but because of presentation mistakes: poor scales, missing units, dot-to-dot lines, and tiny gradient triangles. This guide consolidates every SEAB graph convention in one place so you never lose a graph mark again.

Why a cross-science graph guide?

Graph-drawing rules are nearly identical across Physics Paper 3, Chemistry Paper 3, Biology Paper 3, and all three A-Level Paper 4s. But students rarely see them consolidated - they are scattered across different subject notes, and teachers assume students learned them in another subject. The result is confusion: "Must the line pass through the origin?" is one of the most-asked questions on student forums, and the answer is the same regardless of subject.

This guide covers the universal rules first, then the subject-specific variations.

1 | Line graph vs bar chart - which one?

Use a line graph when both variables are continuous (numbers that can take any value). This covers almost every physics and chemistry practical: time vs temperature, voltage vs current, concentration vs volume.

Use a bar chart when the independent variable is categorical (names or labels, not numbers). This appears mainly in biology: comparing enzyme activity across different substrates, or comparing population counts across different quadrat sites.

If in doubt, look at the independent variable (x-axis). If it is a number with units, use a line graph. If it is a category or name, use a bar chart.

2 | Scale selection

Choosing the right scale is worth a PDO mark in every subject. The rule is consistent across SEAB syllabuses:

Plotted points must span more than half the grid on both axes.

How to achieve this:

1. Find the range of your data on each axis (highest value minus lowest value).
2. Count the number of large squares available on the grid (usually 10–15 on each axis).
3. Choose a scale where the data range covers at least 6–8 of those large squares.
4. Use easy intervals. The only acceptable scale divisions per large square are: 1, 2, 5, or multiples of 10 (e.g., 10, 20, 50, 100). Never use 3, 4, 6, 7, 8, or 9 per large square - these make plotting and reading values error-prone.
5. You do not need to start from zero unless the data includes zero or the physics requires it. Starting from zero when your data goes from 40 to 90 wastes most of the grid.

Example: Your temperature data ranges from 22 °C to 78 °C $range = 56 ^{\circ}C$