Practical skills and data

Revision notes

A strong practical investigation begins with a clear question and an operational definition of what will be changed and measured. The independent variable is deliberately changed, the dependent variable is measured, and relevant control variables are kept as constant as reasonably possible. A method should state suitable ranges, intervals, measuring instruments, repeats and safety controls. A risk assessment distinguishes a hazard from the risk it creates and describes practical steps that reduce that risk.

Measurements should include units and sensible precision. Instrument resolution is the smallest change the instrument can display or distinguish and contributes to measurement uncertainty. Repeating measurements can reveal random scatter and make a mean more reliable, but repeats do not automatically remove a systematic error such as a zero error or poor calibration. An anomalous result should be identified using evidence rather than quietly deleted; repeating the measurement can help determine whether it was a one-off problem.

Graphs are tools for testing relationships. The independent variable is normally placed on the horizontal axis and the dependent variable on the vertical axis. Axes need units and sensible scales. A best-fit line or curve should represent the overall pattern rather than join every point. Gradients should be calculated using a large triangle on the best-fit line where possible. Conclusions should describe the relationship supported by the data and should not claim more precision or causation than the evidence allows.

Variables and planning

The independent variable is deliberately changed; the dependent variable is measured; control variables are relevant quantities kept as constant as reasonably possible. A strong method states how each variable is measured, the range and intervals used, and how important controls are maintained.

A fair test does not mean every variable is literally identical. It means alternative causes of the measured change have been controlled well enough for the investigation to answer its question.

Measurement quality

Resolution is the smallest change an instrument can distinguish. Repeat readings help reveal random variation, allow a mean to be calculated and make anomalies easier to identify. Repeats do not remove systematic errors such as a zero offset or calibration bias.

Accuracy is closeness to the true value; precision is how closely repeated measurements agree with each other (little spread about the mean). Results can be precise but inaccurate if a systematic error shifts every reading in the same direction.

Uncertainty and percentage uncertainty

At GCSE, uncertainty is often estimated from instrument resolution or the spread of repeated readings. Percentage uncertainty compares the absolute uncertainty with the measured value. Measurements that use a larger interval can reduce percentage uncertainty when the absolute reading uncertainty stays similar—for example timing many oscillations rather than one.

Avoid claiming that uncertainty is 'human error'. Name the source: reaction time, parallax, finite scale resolution, heat loss, difficulty locating an endpoint, and so on.

Graphs and relationships

Choose axes so the independent variable is horizontal and the dependent variable vertical unless there is a reason otherwise. Label quantity and unit. Use a sensible scale occupying much of the graph area. A best-fit line or curve represents the trend; joining every point dot-to-dot usually gives a misleading impression of certainty.

For a straight graph, gradient = \(\dfrac{\Delta y}{\Delta x}\). Use two well-separated points on the best-fit line rather than adjacent raw data points. The physical meaning of the gradient depends on the plotted quantities.

Evaluation and improvements

A useful evaluation identifies a specific limitation, explains its effect and proposes a specific improvement. 'Use better equipment' is weak unless the equipment and reason are named. Do not delete anomalies without justification; repeat or investigate them and explain the evidence for treating them differently.

Exam technique

In practical questions, write actions in a reproducible order. Include safety only when relevant and specific. In conclusion questions, describe the relationship supported by the data and quote values or graph features when useful. Distinguish what the results show from what you expected to happen.