S1.3.5—Graphing
- Syllabus
- First assessment 2025
- Objective
- S1.3.5
- Level
- SL
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=kx | y against x | k | expected 0 |
| y=kx2 | y against x2 | k | expected 0 |
| y=k/x | y against 1/x | k | expected 0 |
| y=Axn | logy against logx | n | logA |
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.
Questions calculate a best-fit gradient or draw an uncertainty bar on one point.
Calculate / Draw
Use two separated points on the best-fit line, include units, or draw the full uncertainty range at the measured coordinate.
Using neighbouring data points instead of separated best-fit points or drawing an uncertainty bar from the wrong central value.