Graphs 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.
Learning objectives
- Choose scales and plot points accurately.
- Draw best-fit lines and calculate gradients and intercepts.
- Relate gradient and intercept to an equation of the form .
- Identify sources of uncertainty and suggest specific improvements.
Your graph's best-fit line misses one point by a mile. Should you force the line through it?
Core idea
A best-fit line gives one gradient, but the points could be fitted by slightly steeper or shallower lines too. The steepest or shallowest line that still passes through every error bar shows how uncertain your result is.
Error bars; best-fit line; worst acceptable line. Gradient uncertainty = |best − worst|.
1. Best and worst lines
- Square both sides.
- Plot against .
Best gradient 4.03 s² m; worst 4.40.
- Goal
- with uncertainty.
- Strategy
- Percentage uncertainty carries through.
- Gradient uncertainty.
- From the best line.
- Same percentage for .
- Points fill more than half the grid.
- Gradient triangle at least half the line.
- Read coordinates from the line.
Summary
- Error bars, best fit, worst line.
- Worst acceptable line
- Steepest or shallowest line through all error bars.
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