6.3 - Planning

Syllabus
2021
Topic
6.3
Level
A2

Learning objectives

Choose apparatus from the measurement need

Choose apparatus by working backwards from the variable, its expected size and the precision needed to test the proposed relationship. A named instrument is incomplete unless its usable range and resolution fit the measurement.

Detail Planning question
range Can the instrument measure the smallest and largest expected values?
resolution Is the smallest scale change small enough compared with the measured value?
apparatus dimensions Do length, diameter, volume or separation permit the intended range and method?
measurement access Can the relevant points be aligned, contacted or detected without changing the system?

percentage uncertaintyabsolute uncertaintymeasured value×100%\text{percentage uncertainty}\approx\frac{\text{absolute uncertainty}}{\text{measured value}}\times100\%

For a diameter near 20mm20\,\mathrm{mm}, vernier calipers with 0.1mm0.1\,\mathrm{mm} resolution give an uncertainty small compared with the diameter and are more suitable than a millimetre ruler. A micrometer may be preferable for a thickness near 1mm1\,\mathrm{mm}.

Highest resolution is not automatically most appropriate: the instrument must also have enough range and suit the object. State numerical range, resolution or relevant dimensions when the context makes them important.

Calibration links an instrument reading to a known value

Calibration checks whether an instrument's indication corresponds to known input values. Before measurements, check the zero where appropriate; a non-zero reading with zero input reveals a zero error.

Step Purpose
apply zero input and record the indication detect a zero offset
compare one or more readings with known standards test the scale response across the intended range
adjust the instrument or record a correction prevent the offset entering every result
repeat the check during a long investigation if drift is plausible confirm calibration remains valid

If an instrument reads +0.04mm+0.04\,\mathrm{mm} when it should read zero and cannot be reset, subtract 0.04mm0.04\,\mathrm{mm} from every raw reading. Record both the check and the correction in the plan.

Calibration chiefly addresses systematic error: an offset can shift all readings in the same direction, so taking a mean of repeated uncorrected readings does not remove it.

A zero check is one form of calibration, not the whole idea. A zero reading does not prove that the instrument is accurate throughout its range; comparison with known values may also be needed.

A measurement plan must be executable

For every measured variable, state the instrument, the exact technique and how its reading becomes the required quantity. The description should let another person reproduce the measurement without guessing reference points, timing events or conversions.

Variable Executable measurement detail
diameter or thickness use vernier calipers or a micrometer; close correctly, read at eye level and sample relevant positions/orientations
oscillation period time several complete oscillations between repeated passages of a fixed marker, then divide by the number
count rate count for a stated long interval, measure background over the same interval and subtract background rate
potential difference connect a voltmeter in parallel across the named component and select a suitable range

State how the independent variable will be changed and measured for at least a useful spread of values. Define the dependent-variable reading at each setting and include any necessary derived quantity.

Use techniques that reduce avoidable reading error: fixed fiducial markers for timing, perpendicular viewing to limit parallax, and unambiguous centre-to-centre or end-point definitions for distance.

Writing only 'measure xx' or naming an instrument is not a method. Do not confuse measurement technique with later repetition: first make each individual reading valid, then decide whether and how to repeat it.

Control variables protect the causal comparison

A fair test changes the independent variable, measures the dependent variable and holds other variables that could affect the result constant. For every control variable, state both how it is controlled and why its variation would matter.

Planning move Example for light intensity on a solar cell
identify a competing influence source-to-cell distance also changes intensity
give an operational control clamp source and cell at a fixed measured separation
explain the consequence changing distance would alter the voltmeter reading independently of the chosen variable
monitor another relevant condition exclude or keep background light constant

Choose controls from the physics of the system rather than listing generic conditions. Temperature, alignment, initial displacement, source-detector distance or component values matter only when they can change the dependent variable in that experiment.

A useful sentence pattern is: 'Keep ___ constant by ___ because ___ would otherwise change ___.'. This makes the variable, method and causal reason explicit.

Do not call the independent variable a control variable, and do not write 'keep everything else the same'. A control must be relevant, measurable or enforceable, and tied to the validity of the comparison.

Repeat readings only when they strengthen the evidence

Repeat a reading under the same stated conditions when random variation is plausible and the measurement can be reproduced. Repeats reveal scatter, help identify an anomalous result and allow a representative mean.

Situation Repeat strategy
manual timing or a fluctuating sensor reading repeat at each setting and calculate a mean
period of a rapid oscillation time many cycles per run, then repeat runs
variation across an object, such as thickness measure at several relevant positions before finding a mean
counting random events use a sufficiently long interval and repeat if time permits

xˉ=x1+x2++xnn\bar{x}=\frac{x_1+x_2+\cdots+x_n}{n}

A planning answer should say whether repeats are appropriate, how many or at which settings, what will be averaged, and how an anomalous value will be checked. The choice should match the source of variation.

Repeating does not correct a zero error, poor calibration or a consistently biased technique. It reduces uncertainty associated with random scatter only when the conditions genuinely remain the same.

Safety controls must match a specific hazard

Identify each hazard created by the proposed apparatus or procedure, state the harm it could cause, then specify a control that reduces likelihood or exposure without preventing the measurement.

Hazard Possible harm Proportionate control
charged capacitor electrical discharge keep within working p.d., observe polarity and discharge before handling
ionising-radiation source tissue exposure maximise distance, minimise time and use tongs; point away from people
laser beam eye damage never view directly; keep beam below eye level and use a stop
hot component burn switch off, allow cooling and handle with suitable protection
falling or moving mass impact secure clamps and keep the fall zone clear

Prefer removing or enclosing the hazard and limiting exposure before relying on personal protection. Include only controls relevant to the actual setup and explain what each control manages.

Safety is part of the executable method: specify when equipment is isolated, discharged, cooled, shielded or repositioned. If a hazard remains significant, change the apparatus or method.

Generic phrases such as 'take care', 'wear goggles' or 'do a risk assessment' earn little scientific value without a named hazard and matched control. Do not invent hazards that the proposed experiment does not contain.

Plan the analysis before collecting data

State how the measurements will test the proposed relationship. This determines which raw quantities, repeats, range and derived columns must be collected; analysis is therefore part of planning, not an afterthought.

Stage Planned use of data
process calculate means and required derived quantities with units
display plot the dependent or transformed variable on the vertical axis against the independent or transformed variable on the horizontal axis
test compare the graph's shape, straightness, gradient or intercept with the prediction
conclude state whether the data support the relationship within scatter and uncertainty

Derive the graph from the proposed model. For constant acceleration from rest, x=frac12at2x= frac12at^2, so plotting t2t^2 against xx should give a straight line through the origin with gradient 2/a2/a. For T2=C(2lh)T^2=C(2l-h), plotting T2T^2 against hh should be linear with the predicted sign and intercept relationship.

Plan enough well-spaced values to reveal the trend rather than merely comparing two endpoints. State how the best-fit line or curve will be used; do not promise a conclusion unsupported by the chosen plot.

'Plot a graph' is incomplete unless both axes and the expected test are named. Correlation or approximate straightness supports a proposed model but does not by itself prove that no other physical explanation is possible.