Learning outcomes
- Write a complete experimental plan.
- Choose apparatus and justify it.
- Include variables, repeats, safety and data processing.
- Predict the form of expected results.
- Plan a table and graph before collecting data.
7.1 Begin with the testable question
Translate the task into a relationship: how does X affect Y? Then state the independent and dependent variables and identify the most important controls. This prevents a method from becoming a list of apparatus with no scientific purpose.
A prediction should state both direction and reasoning where appropriate: increasing wire length is expected to increase resistance because charge carriers travel through more material and undergo more collisions.
7.2 Apparatus and arrangement
Select apparatus with suitable range and resolution. Describe how it is assembled so the measurement is physically possible. Include reference points: length is measured from pivot to centre of bob; extension is measured from the same pointer position; angles are measured from the normal.
A labelled diagram can communicate the arrangement efficiently, but it does not replace a written sequence when the question asks for a method.
7.3 Procedure
State how the independent variable is changed and how the dependent variable is measured at each value. Give a useful range, number of values and repeats. Mention when the system should be allowed to settle or return to a starting condition.
Write actions in chronological order. For circuits, assemble with the switch open, check meter ranges and polarity, close the switch briefly, record readings and open it again before changing the wire length.
7.4 Recording and processing
Design the results table in advance with quantity/unit headings. State what calculation will be performed, such as resistance V/I, period total time/number of oscillations, density mass/volume, or temperature fall.
State the graph axes and what feature will answer the question. If testing proportionality, plot the dependent variable against the independent variable and judge whether the best-fit line is straight and passes through the origin within experimental accuracy.
7.5 Safety and evaluation built into the plan
Include relevant precautions, not a generic safety sentence. Also anticipate the main uncertainty and design the method to reduce it through repeats, larger measured quantities, pointers, insulation or lower current.
A high-quality plan is reproducible: another learner could follow it without guessing essential distances, quantities, timing intervals or calculation steps.
Worked examples
Plan skeleton
Change X through six evenly spread values. At each value, measure Y using stated apparatus; keep A, B and C constant; repeat Y three times and calculate the mean; record X and mean Y with units; plot mean Y against X; use the graph to identify the relationship.
Testing direct proportionality
A straight line alone is insufficient. The plan must include the origin or a suitable low value and use a best-fit line to determine whether it passes through the origin within uncertainty.
Practical focus
Investigation or training activity
Write a full plan to investigate how the length of a pendulum affects its period. Exchange plans with another learner and identify any step that would force the reader to guess.
Examination guidance
- Include at least five or six values unless the context prevents it.
- State the range or how it is chosen.
- Name the graph axes.
- State how repeats are processed.
- A plan must contain a conclusion method, not just data collection.
Check your understanding
- What should be identified before choosing apparatus?
- Why should the results table be planned in advance?
- What makes a plan reproducible?
- How would you test direct proportionality?
Answers
- The testable relationship and variables.
- It ensures all required measurements, units and derived quantities are recorded.
- Another person can follow it without guessing essential details.
- Plot dependent against independent and see whether a straight best-fit line passes through the origin within uncertainty.
