Lab Skills: Designing a Controlled Experiment

A real experimental question starts vague: 'what affects resistance?' Designing the experiment means narrowing that to one independent variable you deliberately change, one dependent variable you measure, and a list of everything else that could plausibly matter, which you hold constant. If you change two things at once, say wire length and wire thickness, and resistance goes up, you cannot say which change caused it. The data can look clean, a smooth line, small scatter, and still be useless, because the question it answers is not the question you asked. Good design happens before you touch the equipment: list variables, pick the one to vary, control the rest, and only then collect data.

Take resistance and wire length. You want one spool of wire, same material and same diameter, so thickness and resistivity are fixed. Cut pieces of different lengths, keep temperature constant since heat changes resistance, use the same ammeter and voltmeter so instrument error does not shift between trials, and apply the same voltage range each time. Vary only length, measure resistance at each length, then graph resistance against length to look for a pattern.

This connects directly to error analysis. Repeating a trial at one fixed length several times shrinks random scatter, the jitter from reading a meter or a shaky connection, but it does nothing for a systematic error, like a voltmeter that always reads 0.2 V high. That bias rides along in every trial equally, so averaging never exposes it. Controlled design and error analysis also meet when the controlled variable itself is not staying controlled, which the next idea tackles directly.