S1.3.5—Graphing

Syllabus
First assessment 2025
Objective
S1.3.5
Level
SL

Read and Linearize Graphs

Build a graph that exposes the relationship

Put the independent variable on the horizontal axis, label both axes with quantity and unit, choose scales that use the plotting area, and show uncertainty bars where available. Use a line or curve of best fit for the trend; do not join each point.

Predicted model Plot for a straight line Gradient Intercept
y=kxy=kx yy against xx kk expected 00
y=kx2y=kx^2 yy against x2x^2 kk expected 00
y=k/xy=k/x yy against 1/x1/x kk expected 00
y=Axny=Ax^n logy\log y against logx\log x nn logA\log A

Extract meaning from the fit

Calculate gradient from two well-separated points on the best-fit line and include its units. Use maximum- and minimum-gradient acceptable lines through the uncertainty bars to estimate gradient uncertainty; apply the same idea to intercepts. Interpolate within the measured range cautiously; extrapolation relies on the model continuing beyond the evidence.

Example — test an exponential claim

For exponential decay, equal time intervals should give approximately the same multiplicative factor (or a constant half-life). Alternatively, a suitable logarithmic transformation should be linear. Agreement must be judged with the uncertainty bars, not from visual closeness alone.

Interpret, do not merely describe

A gradient is a rate of change; a changing gradient shows a changing rate; an intercept is the predicted value at zero input; maxima/minima are turning points; and an area under a graph is an accumulated quantity only when the product of the axis units represents that quantity.

S1.3.5 Exam Analysis

Assessment in practice

1–2 marks
How it is assessed

Questions calculate a best-fit gradient or draw an uncertainty bar on one point.

Command terms

Calculate / Draw

What earns marks

Use two separated points on the best-fit line, include units, or draw the full uncertainty range at the measured coordinate.

Watch for

Using neighbouring data points instead of separated best-fit points or drawing an uncertainty bar from the wrong central value.